{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "856d21c5",
   "metadata": {},
   "source": [
    "### 6.算法和处理步骤\n",
    "\n",
    "* **核心公式**\n",
    "\n",
    "正向计算(第j层的输出$y_j$）\n",
    "\n",
    "$$\n",
    "\\vec{y_j}=f(W_j\\cdot\\vec{x_j})\n",
    "$$\n",
    "反向训练\n",
    "$$\n",
    "Output\\rightarrow\\delta_j=(t_j-y_j)y_j(1-y_j)\\\\\n",
    "Hidden\\rightarrow\\delta_j=a_j(1-a_j)\\sum_{k}\\delta_k w_{kj}\\\\\n",
    "k\\in Downstream(j)\n",
    "$$\n",
    "\n",
    "迭代公式\n",
    "\n",
    "$$\n",
    "w{ji}\\leftarrow w_{ji}+\\eta\\delta_jx_{ji}\n",
    "$$\n",
    "\n",
    "```\n",
    "# 每次训练\n",
    "for k in range(epoch)\n",
    "    # 正向计算\n",
    "    for j in range(NN_depth):\n",
    "        # 式2 ( a = xxx)\n",
    "        X_j = f( W_{j, j-1} X_{j-1})\n",
    "\n",
    "    ＃ 反向误差计算\n",
    "    for j in range(NN_depth, 0, -1):\n",
    "        # 式3， 式4\n",
    "        delta = y_i(1-y_i)(t_i-y_i)\n",
    "        or \n",
    "        delta = a_i(1-a_i) \\sum w_ki delta_k\n",
    "\n",
    "        # 式5\n",
    "        w_ji = w_j + epsilon delta_j x_ji\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ddb818d",
   "metadata": {},
   "source": [
    "这里演示的代码比较死板，程序架构是一个固定的，实际上可以通过写循环来让这个适用于多层的神经网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "35cadb57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "\n",
    "import numpy as np\n",
    "from sklearn import datasets, linear_model\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.metrics import accuracy_score\n",
    "\n",
    "# generate sample data\n",
    "# 使用的数据集是相互交叉的\n",
    "np.random.seed(0)\n",
    "x, y = datasets.make_moons(200, noise=0.20)\n",
    "\n",
    "y_true = np.array(y).astype(float)\n",
    "\n",
    "# generate nn output target\n",
    "t = np.zeros((x.shape[0], 2))\n",
    "t[np.where(y==0), 0] = 1\n",
    "t[np.where(y==1), 1] = 1\n",
    "\n",
    "\n",
    "# plot data\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y, cmap=plt.cm.Spectral)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "a9267ad5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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QJWf3NU3LGSPY+thnbtslo4Hm06pWCNXisuG0uMxdwOySFW+zcuLTOPMKXAVYmsbQOU+US5Tu5IK1JfYpiP5yCalbDzNxy8d6e0OdaqWmHP5CYKYQ4megP5ClaZpbOEenZuhw1yRO/b6e1O3ROHMLMPiaEbJM86lD+L3brWiKQutrx9D5gekeF2LrAqYgf8b+8w6rr3ylUD9Hw795BCN/eb7MnP+CpHTsmXkEtI5CKqNS+GxCe7djRtxcUrYcQrHaCR/YCdlcvqIrg58FJMlj0xXNqZAVHUfCyh00vrhyImw6OuXBK4VXQoifgBFAKJAEPA8YATRN+6QwLfNDXJk8+cBNmqaVWVGlF15VH5qqkvjPTpLW7cMS0YCTC9aQvPFA0axf9jHRoEtLJmz4oM6mHDoLbJxeswdbahahfTsQ1K5Jqcfb0rNZfdWrnF6zG8noqpYd+NH9tJoxstptTdsVw6LB96EUuK+dgEsaovcrN9P1sSur3Rad85vSCq+8MsPXNK3Ujs+a66ni3fp6nTKxWR1kpBfQIMQXs7n4j1pIElGjexM1ujfJmw6w7bFPi4V4lAI7mQdPEbd4M80mDnLp3VvtyBZTnWiwfWLBWtbe+CaiMHNGGGRG//4yEUO6lnjOysnPkrr1EKrdWaRpv+6WtwloGUlYNbc1DOnRht6v3cLWxz71qPQp+5jwr4Z+BTo6Z1NTIR2dGkRVNebO2c7fS6KRJIGmalwyqSPTr+nh0VmnbDyA6sEJOXMLODBrAXlxKex5/UcKEtMxBvjQ5bEr6fb4VbXm+HNPJrHmutfdZssrJjzJjPhfPS5+ZsfEk7bjiFu1rVJgZ9///cLIn5+rVpsBOt8/naaTBvJH99td6wCFL9eu1oq+NJs8qNpt0Lmw0R1+DbF7Wzx//LqHtJQ8WrcLZfo1PWjcNBgAVVHJzbHh62/GYKj6ot2f8/byz9JoHPb/nPiyPw8SEGjhkkkd3Y73iQpBMhtQ7e7ibKf/3U3iPzuLvrdn5rHnlR/QHE56PHt9lW2tDDHfr0BT3B9Qmgan/lhP62tGu+3LT0hDMhncQyqaRtbhWPb/bx6aptF8ymACWkVVl+kEtoxi0vZPWHfTW6RsPQRAxOAuDP368WpLYdXROYMunlYDrFkZw3efbynKpRcCTGYDz705lkP7kpj/424cdieSJHHJpA5MvaoHkocin/Jy1zVzyc9zrxgNCrbw/jeXu213Wu380uxKbGnZ5U7LNAT4cE3aHxVa9PQWmx+ezQEPKZKyj4m+b99Jx7snu+2zZeYyN+pyFOs590WWEEIgZAk0EJKg1ys30+Uh9/sErnz6E/PWEP3FIlSnQpvrL6b1NaMrdR8cOfkghJ6OqeNVqj2Gr1MyiqLy8zfb/yucwuVT7TYnn72/gcS4rLP2qSxdeBBZlphyZfcSr6mqGutXHWPV8micDpVBI1oxamw7TCYZVdU8OnuA3BzPC4YGi4nx//6PVVe8ROahU6C4Z5K42WB3Ys/MxRIaVOax3qbJ2L5Ef/aXxzTHqNG9PJ5jDvan62Mz2Pfur/+dZ5DAqaJBsU5XO575iqYTBxLU1n0ReN1Nb3Fi/pqia6RuOcTxuasZs+i1Coe4SmrkkhUdy9635pK+K4aQXm3p8ugMj7bo6FQUPem3mslMLygWWjmDpkHs8YxiDwIAu01hyR8HUdWSZ9qf/m8d3322haOHUzl5LJ353+/kjWeWoygqkiSIbBzo8bymLRqUeM3gjs2ZuvdLOtw50aOEwLkYfC2YGvhjS89m77u/sOaGNzjw/gLsWbllnltVokb3ptHIHsU6UBn8LLS7ZTxB7ZqWeF6P529gyFePEdqvAwGtIgnv3wnJ7B5G0RSVkwvWum1P332U4/P+ddPTSVq3p1jYqyqkbD3Ewt53EjNnGWk7jnDk66Us7HUHqdsOe+X6Ohc2usOvZvwDTCXq05S03W534vAk5QvEnshgx+ZYbDbnWccrxJ3KZNfWOACuva0vJtNZIQYBJrPM1TeXnePd7pbxrs5OpWDwtdDrpRvJOZrAvHbXs/O5bzj63Qq2P/UF89pdT86J02WOUxWEEFz020sM/uIRmkwYQPNpQxgx9zn6z5pZ5nktLx/OxE0fcVnM97SYNtTjcRqaxzrwxFW70Dy8/ThzrSSs3F6pz3Ium+79wKVxVDiOpqg486xsuu8Dr1xf58JGd/jVjNliZNCIVhhNxWO8JrNMeKRneYTAQAsms+doW/SBZI+aFDarkwN7XI62S48oHn9pDF16RNIw1JfuvRrz1KuX0L5z2b1XQ3q0ofNDlyH7uIqxznR38m0ahmwxEdA6ioEf30/He6aw4a73sGfkFi2EOvNt2NNz2PzAR2WOU1UkWabVjJGM+fNVRs17kabj+1copGJNzSJ20cai9Mxi1zbIHqt1zQ0DkIzuPxfZYsLshdCW4nSWOJNP3arP8HWqjh7DrwGuv70fmgYb/z2GJElIsuCya3vStHkw77z4N/azQj4ms8yVN/Uu0XkFBluQZcG5bspglGgQ8t/iX5sOYTz6gnu2Snno/dLNtL5yFCd/X49kkGlx+XA3+QBNVTn97263RV5NUYlftrVS49YUmqaxdPQjZB085bZPMhvp8dz1HkNDzacO8TjTFpKg9dUXVdqe7Jh4Ntz5PxJX74ISQnklxft1dCqC7vBrAINR5paZA7n6lj7kZFlpGOpXlH756Iujmff9TuJOZhIW4c/Uq7rTo0/JC3Q9+jbBYJCBc1oJShJDRrb2ms3BnVoQ3KlFyQcIgWSQPXaRquvphSmbDpBzLNGtW5WQJdrdMo5uj3uuIzQG+HLx0jf5e8qzLllm4TpnxE/P4hsZUilb7Fm5/DVwJraMnBKdvexjpsNdk1CdCmnbo0EIQnq3rbMV0Dp1F93hl5PcHBsb1xwnPTWPth3D6dG7MZJcsYiYj48RH5/izrBdx3CeerVstcUzOJ0qDzw1nM9mbSAzowAhBGazgbsfGUpww5qbBQohaDljJMfnri6Wvy+ZjbS+vvrVMitKfmIaWx6ZTeyfm9AUtVhWzhk0RcWanFnqdcIHdGJG/C+kbj2M5lQI69/RY5inPNizctl4zywc2fkenb3Bz4KmqLSYPpTIUT35OepyVJsDDQ2Dj5lRC14iohqay+icv+gOvxwcj0njzWdXoCgqdruCeUk0kY0Deeq1S9wkC6qLzIwCPp+1noN7k0BAZONAbr9/MOGNAmjaPBhJllAUld3b40mMyyKqSRDdK/FQqgj9Z80k88AJsg7HFYV2GnZvTZ/Xb6u2MSuDM9/Kn/3vpuB0hkdHfwaDr5nwwW4dOt2QZJnwAVVTL034Zyd/T34GxebwaJNkMdH+jol0eeQKJIPMry2vLp4dlFPAinGPc8Wpn0ts2qKjcy66wy8DTdP46O01FBT8N4u1WZ3Ex2ax9I8DTL7CvdGGt1FVjdeeWkZKUm5RumbcyUy+/GAjb82ejJAEWZkFvPLkMrIzC7DbFExmmeAGvjzzxiUEBFaP4qU52J+JW2aTvPEA2YdjCe7cgtC+ZTcUr2mO/bwKe0Zuqc4eQJgMtL2x/G9blcVptfPPtOdKlEsGQNNI+HsHaTui8W8WgeZJZVN1FYG1u2V8NVqrcz6hO/wySE3OJSvDvbOSw66wYfXxGnH4h/adJiujwC033+lUePP5lSTGZ6M4izsEa4GTFHsu33+xlbse8px+6A2EEEQM6lynQwtpO4+U7lwLUW0Oktbto+mEAdVqz+nVu0o/QBKoDicZu4+6vjUa3NYbwNXdy5qaVQ0W6pyv6GmZZSBJUolqA2XJHzidKru2xrFqWTSnjpfW8rd0UpJyPdrgcKjEncx0c/ZnUBSV7RtjPe67kAju2By5HLr+SoGdHc9+Xe32lPamISTJ1QTlrIe7J2cPrsXxyJE9vW6fzvmLPsMvg5AwP8Ij/YmPzSpWjGMyywwf06bE85ISc3jtqWVYrQ5URQMBXXtGcc+jw5ArGFdv0TrEVQxUCSp73vlE62tHs/P5b1CsthIzYc6Qc6z6G7E1GtEDzcND2uBnocn4/pz49V/3kwRIhv9m+gY/C03G9at2WWed8wt9hl8OZj42nIAAMxYfAwaDhNlsoF3HcEZPKPmP7cO3/iUrswBrgRO7XcFuU9i7M4F/lkZXePzmrRrSvlNEseItUY6fnCQJevbVNVhMgX5cuvFDGg3rhpAlhEEqMbMmqGP1t3g0+vsw5OvHkH1MSIUprAY/C00m9Cd8YGdkH7PbObKPmdbXjSFiWDcajejOoNkPMOLnZ6vdVp3zC10ts5zY7Qo7t8SSkZ5Pm/ZhtG4XWuLiZHpqHo/d9QcODxrzTZoF8+r7Eys8vsOhsGj+PlaviMHpUGjRuiHRB5Kx2TyHB8wWA/7+Zp57exzBDXQ1xjOoDicIweHP/mLrOU1fZB8zY/56tcbCJLknkzj64984snJpMn4AEUO7YkvN4tdW17itORgDfLki9mdMgX41YptO/UVXy/QCJpNM/yEtynWsw6FSUqKKo4xMkZIwGmWmXNm9SEVTVVSevO9PUk7nohTqrggBvn4mho9pS7OWDegzsBlGo8z2Taf445e9ZKTl07p9KJdd04MmzUsWUqtPqIrCntd/4sCs+dgzcwnp1Zb+s2aWmDZ5Zmbf8e7JGP0t7HzpO/LjUwnu0Iy+b99RozFx/+YRdH/y6mLbLGHBjF74CquueKmwqE1D9rVw0YIXzytn7yywcWj2Qo79/A8GXwsd7ppEyytG1LkMr/MNfYZfDWiaxsO3/0ZaSl6x7UajzPhpnZh2VQ+vjJObbeOHL7eydcMpNE2jZ78mXHtr32IFWH8vOVxMnrlIi/+tcTRpFuwVO2qTDXe9x5FvlqCeJSZn8DVz6aaPaNClZS1aVjWKqmolQWjvdq6F3PMExe5g0aB7yTx4qkiHyeBnofX1FzPoo/tr2br6T2kzfN3hVxNHDiXz9gt/oyoqDoeK2WIgLNyfZ94c61ZtW104nSozr/+FgvziyjtCQK/+zbjvieE1Ykd1kXk4lt863eiubCkELWeMYMSPz9SGWTplcOynf1h/x7s4c4uHrWSLian7vqzWjmPViS0zl+T1+zAF+RE+qHOtPaT1kE4t0LZDOG/NnsL6f46SkpxLhy4R9BnQDIOx5vRPMtLyXBlC56BpcDQ6pcbsqC423vU/jzLGaBrpu4+iKoqrm9V5NDs+H4hfttXN2QMIg8TptXvrpcPf//58tj/xBZLJiKapmIL8uGTpm6XrUdUCusOvRoIb+DBhetml+iVxpnuVj6+xwqmcAAGBFlQPFZrgSjetz6iKQtK6fSXut6Xn8K1lLAhBs8mDGPTxA1jCgmvMPmtKJvvfm0/8iu34NQ2jy8NX1OnitJrEJyrEYzGZEBI+4cG1Y1QVSN64n+1PfYlitRe10HTmWlk29nGuOPFTnZpw6A6/jrLun6PMnbOD/Dw7skFi9Pj2XHZNjwpp41h8jAwc3oqNa44X67plMstMvrz6K4S9RdquGOKXbcUU6EeLy4e72ipqlNp/15qSWZRzf2rhBjL2Hmfq/q9qRGGyICmdP3rcji0zF9XmIG17NPHLtjJo9gO0ue7iah/flpnL0R9WknXoFGF9O9DiihEYymhqU5O0v3U8B2YtgLMdvhAY/CxEjSm7SU9N48gt4MT8NRQkphM+qDMRQ7sWW1w++PEfLvXUs9E0HFl5JG/YT8SQrjVsccnoDt8LZGYUsODHXezcEofZYmDU2HZcMqljpWblADu3xDLnk81FOvlOp8qKRYfQgBnXe+7ZWhI33NEPSRKsX3UMIcBokplxQy+692lcKdtqEk3TWH/7uxz76R9UuxPJZGDLo59w0fwXaXxJXxqN6MHpVbvcdWZkAWeFsjSHQn5iGgkrttNkbL9qt3vPmz9jS8/5bwaraSj5Njbd9yEtZ4ysVvnozIMnWTT4PhS7AyXfRoz/cna+OIeJmz+ulf7DnghoFcXIX55jzfWvozlVNFXFJzKE0QtfqVQz+OokffdRlox6CNWhoBTYkH1MhPXryJjFrxf9HO0ZOZ4nH0LCnpXnvr0W0Rdtq0hBvp0nZi4kJ8uKUuhkTGaZHn2acM+jwyp1zeceWsTJY+5SDCazzMffz8BYiXUAm9VBXq6doAY+lX4Q1TSxizax+sqXPeakX5k0n4LENP4aMBNnvhVnnhWDvwWEwJnjrn0kmY30eeM2Ot8/vdrtnt/xRrIPu0taGAN8GL/ufRp2bVVtY//Z/25St0UXc0CS0UCbGy5m8GcPV9u4lUF1KqTvikH2MRPcqXmdS8nUNI0FHW4g+0h8se2yr5leL99MlwcvAyD6y8VsfuAjt99T2WJiRsKvmINrVs20tEXb+vGXX4dZ8/dR8vPsRc4eXI3Id26N43RCdqWumZbiuRG4pkJ+nt3jvrIwW4w0DPWrN84eIGbOMs+iZ8IlQBbQMpLLjn5P//fuofNDlzHo4wfoNHMqwsNnlIyGGkvT9AnzPJNWHU4sIZ4bzHsDR24BaTtj3GabqsPpsSl7bSMZZEL7tKdB5xZ1ztkD5BxLJC8+1W27km8j5uulRd+3vnY0QR2bYfAr1GsSAtnXTJ83bqtxZ18Wekinihzen1SU4342siw4cTSNRlEV/wNv2qIhB/e6NwI3mWUCAtzL7s9XSn37LNxn9PcpkgdO3rifdXf8n1ujcWGQCWgdReTIHtVlajG6PDKDtB0xOPP/e1hJRgNhAzrhGxVabeMKSSCE58QlUckmLRc0pfz+nf27KZtNTFg7i6M//M3JBWswhwTR4c6JhA+se4v09We6V0eJbBxY1K7wbFRVw2Z1smZljKvxeAVCZ5df1xOT2b3p+fQKLtrWFxS7g5N/rOfQJ3+SvvdY0fY2113836zpLDRVo9GIHm7btz35Beq5i2e4ZpLj/nm3xrIlmk0aRLdnrkH2MWEM8kP2MRPatz0jf3m+Wsc1+FpoNLIn4pw4uGQx0eb66l8sPt8IaB2Fb6OGbttlHzNtbih+P2WziXY3j2PMX68zbM4TddLZgx7DrxCH9iexZmUMDrtC/6Et6NWvKRlp+Tx570Js1v8yDiTJ1cdWINDQXJrxkQE88fIY/PzLN0OPOZzCL9/u4NTxDBqE+DJlRrdySzvUJ7IOx7JkxIM4822oTgUENJ0wgOE/Po2QJNbe+CYn5q9BsTqQTQYQgpFzn6XppQPdrvV98CQc2e6LZJLJyJUJv2BuWH3hFE/Ys/PI2HMMn0YNCWzj3UVyp9UOmqvV4dnkJ6axaMj92FKzUB1OhCzRsEcbLln2JoZySETrFCd1RzRLRz2CpiiF60Q+NOzRmrEr3kY2153Mp7PRK229wPwfdrJ04UFX5ozmEifr3D2S+54YTszhFD5/fwNpyS5nExhsITvTivMsCVyDQaLvoObc+dCQStuQEJtFQmH7wqimFc+4iDmUwurlR8jPt9NvcHP6Dmpe6zH937rcTObBU8Venw2+Fvr93120v/1SAFK2HiJ+6VZMQX60nDECnwj3WRfAb11vIXP/CbftBj8L16T/Uenes3WJvPgU1t38DomrdgIQPqgzQ754pNgDRVUUEpZvI+dYIg17tHFVfdbBGHl9wZ6Vy/G5q8lPTCd8UCeiLupVp3Lrz0V3+FUkJSmXJ2f+gcNRPDZsthi474nhdOkRhaZp5GRZMZpkHrx1gZucAYBskPjy16sr/MdntzmZ9fpqog8kIxf2rm3XKZz7nxyBqZw9dRf/vp/fftqNw66gFT6wWrUN4dEXRtea0885lsBvXW8t0lM5m4Y92zB5+6cVut7xX/9l7U1vFlfA9DXT+f7p9H71lirbW1PYMnORZAljQPGm9KrDyby215Efn/rfOoUkMIcEcvmxHzD66aqoOnqWTpXZvzsR4aG7lc3qZMeWOMDV6i8w2AcfX1Oxmf3ZqIqKVkYDDk/MnbPDtThsVygocGC3Kxzen8TcOTvKdX52ZgELftiN3aYUTaRtVifHjqSxfVPtdcRSbA6P9xUoVIqsGC0vH07//92NqWEAssWEwddCp3un0fOlG6toac2Qse84f/S+k58jpvNj6FSWjn6EvPj/JDBi/9qEPSOn+KK06srxPz53dc0brFPvqP/vuKWQkpTDiaPphIb706J1w0q/1lp8DB7bGcqywNfXvYimW88odmyJLbbILwS07xxRqUXXtf8cdXu7cDhU1v5zlOtuL7uQ6OC+JGSDwHHOS4fN6mTbxlP0G9y8wjZ5g6D2TTEF+XnMX2519ahKXbP9bZfS9uZx2NKyMQX7V2uRkzexZeSweOj9xQp1Tv+7m8VD7md6zHdIskz20QQUq/ubozPP6pYrXh6SNx3g4Ie/k5+YRrNJg2h3y3iM/vpbQlXRNI2cowlIJgP+zSJq25xinJcOX1VUPn9/A1s3nsIgS6iaRkRkAI+9OJqAwIovXPXs2wRPnU4lWWLIyNZu26+5tS9HDqVgtTqw2xRMJhmjSeamuyrXHPtsWYTybD8Xi48RcH9gCUng6+/uEI8dSWXe9zs5dTyD0HB/pl7ZvVoqc4UkMfzHZ1gx4UlURUW12jH4+xDYtjGd7ptW6etKsoxPePXp/Tty8snYfwLfqBCv/UHHfLcC5Zy3Gk1RsaXnEL9sG03H96dh91ZIZqObBo3B34eQniW32/TE4S8WsfmBj1ySAJpGyuaDHJq9kElbZ7uFknTKT9L6ffx79atY07JA1Qhs35RRvz7v9UX7yuKVkI4QYqwQ4rAQIkYI8YSH/SOEEFlCiF2F/57zxrglsWLRIbZtOoWjMARiszqJP5XJZ++tr9T1zBYjDz4zCh9fIxYfAxYfI0aTzI139adRY/fMj5AwP96aPZkrru/FkJGtmH5ND96aPcXjseWhXadwj9vbl7D9XDp3a4Qsuzt8o0FixJi2xbYdjU7h9WeWs3/3aXKybRyPSePDt/9l/epjbuefS8b+E6y+5lUWdLyRf654kbSdR8o8p9GwbkyP/pYez11H+zsnMuTLR5m46aM6G4/e/er3/NToMpaPfZwFHW5k6ZhHsGd5LpSrCNlH4jyuZagOJ7knXDUZURf1IrBtYyTzfw9pyWjAp1FDmk0ZXO6xHHkFbHngI9daR+FrqJJvIy82mUOf/FnFT3LhYE3JJP/0fxXx+afTWT72cfJik1HybShWOxl7j7F4+AMlNqKvaao8wxdCyMBHwBggDtgqhFioadqBcw5dq2napVUdrzysXBztVgylKBoH9pymIN+Oj2/F06k6dI7ggzmXc2DPaZwOhU7dGpV6HR9fE2NK6XlbEdp1CufQvqTiGwVMv7ZHuc43GGUefWE077z0N87C0JCiqMy4sTctWocUO3bunB1u985uU5j7zXYGDmvpMbQFrkyapaMeRimwo6kqWdFxxC3ezJi/XiPSQ8782fhGhtD9iatLPaYucGLev+x5/SeUAhtKoXpD0tp9/Hvd64xZ+GqVrh3Wr6Orsvgc2WAhS0WzdyFJjF/9P7Y/8xXHfvwbTVVpcdlwer92S4VCV2k7jrjl6gMoBXZO/raWro/OqNJnOd/JOZbA6qtfJX3XURAQ2DqKYd8/Rfyyra7U4rNRNZy5VuKWbqHZxEG1Y/BZeCOk0w+I0TTtGIAQ4mdgMnCuw68xbB7inAAIsNkUfCr5xmo0ynTvXbOvZjabk2V/HHTbbpAldm2NIy/XzumEbJo0C6ZTt8gSHXLLNiHM+uoyDu9PwlrgoEOXCI81ASePZXg8Py/XTn6eHf8SKn3dtETOCIbd+z5T935Vjk9a99n7zi/FqmcBVLuDhBXbsaZmVUmcrMXlw9n14hzy7ClFC9ayxURI73aEndWu0Rjgy4BZMxkwa2alxzIF+7tVI5/hzGfIT0jFmW8joHWUntJ5FordwaKh91OQlFGkxpp54CRLRj5E82lDUW3uvkdVFPIT0mraVI94w+E3Bs5O9YgD+ns4bqAQYjeQADyiadp+TxcTQtwO3A7QrFmzShnUvU8T1q066tb8o2GIL0HB9av4JO5kBpKHcIzTqbL0j4OsXHwYp0PFYJAIa+TPU69egq+f5zcPg0Gic/fIUsdrGOJLQlyW23bZIBWuBXgmbXu0x+2ZB06hOpU6p4JYGazJnh+GkkHGlp5dJYdvsJi4dPNHrLvlHeIWbUJTVDRNI2JIFzRVRXhR1rlBl5b4NYsg+3BsMaVRg6+FljNG8ueAe0jffRRJljA1CGDYt0/UaK/fukzcos04cguKnP0ZVIfTVQjn74Mz1128L3yg5x7LNY03YvieHv/n5h7uAJprmtYd+AD4vaSLaZr2maZpfTRN6xMWFlYpg6Zf3Z2AQAsmk+uPRJYFZouBW+4dVO9mKwGBlhLTPJ1OFWuB0/W/1UliXDY/f7O9SuNNntHVo6zD6PHtPUpInMHcIMDjdoOfxaOYWX0kanRvj6EQyWz0Spem3BNJJKzcXjT7Vm0O9r83ny0Pflzla5+NEIIxi14joE0UBn8fjIF+yBYT3Z+9lh3PfUPa9mhUmwNnvo38+FRWTnqG3JNJZV/4AiD3VJLHlGEl34YxyI+Alo2Qz+o9IPtaaDK2Hw27uSd31Abe+EuMA5qe9X0TXLP4IjRNy9Y0Lbfw68WAUQhRbSpSwQ19ef2DSUy9qjs9+jRmzKUdeOW9S+nQuWZTpPJy7az5O4blfx0kMd591lwejkanopYzd9/pVNm87mSZxyWfzmH+Dzv5+uNNbN90CvWs1/sBQ1sy4/pe+Pq5FqZNJpmLxrmar5RGpwcvQ/YtHu6Rfc10nDml3j1kS6LHc9djCvJDMhW+GBeqIg744F6vvMHsevk7t0YaSr6N6C8We2Vh+GwCWjRi2sFvGLfq/xg591lmxP9CWL8OWFMz3cI9qsPJ4c8XeXX8+kpo3w4ef9YGfx8aDe7ChPUf0PXxKwls14QGXVvS963bGTH32Vqw1DPeCOlsBdoKIVoC8cCVQLEVOCFEIyBJ0zRNCNEP14OmWoNafv4mxk/tzPiptSNitH93IrNeWw3ClSb6y7c7GTW2HVfd1LvcDnDrhpN89eFGlHNm+JLkSq7wVCRdUkvDM2zbdIpP/28diqKhKCob1xyneauGPP7i6KJ+u6MndGDk2HZkZ1nx8zcXvSmVRtdHrqAgMY3Dn/6FZDKg2p20umoUvV66qVyftT7g1ySMKXu+YN+7v5D49078WzSiy6MzvNa6MHP/CY8/VMloIC82BVOQd6R28xNSyY5JILBNFKG92/23PT7Vo9SmaneSezzRK2PXd8IHdiK0XwdSNh0syqqSzEb8m0fQbPJgJKOBns/fQM/nb6hlSz1TZYevaZpTCDETWAbIwFeapu0XQtxZuP8T4DLgLiGEEygArtTqsqZDOXE4FHZsjiUpMYemzYPp3rsxkixhtyu8/8a/2GzFX/1WLztC996Ny4yjn2HeD7uKul6dja+fieatGnJgb1Kxyl1JFvTq19Tt+LPt/XzWhmLXtFmdnDiaxrrVx4pSNDVNI+V0LhoawQ3Klx4pJIn+/7uHHs/fQO7xRPybR9S4WFlN4BsZQr937qqWazfs1oqcY4ke9ez9m1f97VR1OFl781ucnLcGyWJCtdppPn0YQ79+DMloILR/R7Rzs0xwheUiR124MXzF7sCekYM5JAjJIHPx4tfZ9+6vRH+1BM2h0OrqUXR78up6odXkFQsLwzSLz9n2yVlffwh86I2xqpu4kxn8+t1OYg6nEtTAwsTpXRk43L1xRlpKHi8/voSCfAc2mxOz2UDDUD+eeeMSYg65N00AV8bNun+OltvhnxFjO5e8XAfX3taP159ejs3qdI1vMeDvb+aqm0vuCXo0OtXjgovdprDx3+OMGNOWk8fS+eDNf8nKdC08BQZZmPnYcFq2CfFwpjvmYH/MPduWfaCOG92fvY74ZduKZQIZfM20v2OiV4qhdjz/DScXrEOxOVAKs0lO/rYO/2bh9H7tVoLaNqH5ZcM4tWBdkQ2S2YhPZAitrr6oyuPXNzRVZeeLc9j/f/PQFBXZbKTHizfQ+b7pdH/qGro/dU1tm1hhzo/VNC+REJfFS48vZdf2eHJzbMSfyuKrjzeyaIF7QtFXH20kK9OK1epE08BqdZJ0Oodfvt2JqqoeHSuAs4R0OE+ER3peCA0IMhPZOJB3Pp3Ctbf1ZezkTtxwZ3/e+HhyqTNyo1FC89geA0xmAwUFDt54ZjkpSbnYbQp2m0Jqch5vPrei0p22dMpPSI82XLzsTUL6tEMYZCxhwXR/7nr6vn2HV65/aPZCt+IupcDGwdkLi74f9s3j9H33Thp0bUlA6yg6P3gZE7d87CbDfCGw+7Uf2ffurzjzrChWO/asPHY89SUx3y6vbdMqTd1/B6lBfv95d5H88RnsNoU/ftnDmEs7FMWynQ6FA3tOuy2mKk6VLetPcNVNvVE8xNLNFgMDh5W/zd4V1/fko7fWFAvBmMwyl1/TAyEEZouRYaPLX1Lfsk0oFh8j1oLioSaz2cDIi9uybcMpFA8LxKqisWX9SUZcrM/cq5uIwV2YtGV2tVzbkZNf5nYhSXS4YyId7phYLTbUFzRVZd+7vxRTXgVw5tvY9fJ39bahjD7DP4uj0ake1SyFgNTkXDLS81m5+DDL/zpU4jU0zaVdc+u9gzCZ5KJURrPZQI++TejRp0m57TnTCD2qaRCyLAiL8OemuwcwbEzlHK8kCR56ZhR+/iYsPgbMZgNGo8zQi1rTs18TMjPyPerz2GxOMjPcc4t16iYFSelEf7GI6C8XU3BW7UBYP8+V3yVtv5BRrHaP+fRAnSmiqgz6DP8swiICSPUQN1ecGgf3nuanr1057pqmoWmaq3/oWc8Hg0EqUp7sP6QFrduFsnHNcQryHfTo04S2HcMqnKLYo28TevQt/0OiLJq3asisry9j9/Z48nJsdOjSiIjC0FHbjuEYTXKx7l3gejNp26FyNRE63sNptePMK8DcMLDE36Por5ew6Z73i2ofNt37AQM+uo92N42j3//dzdLRj6DanWhOBWGQkc1GBrx/b01+jHqB7GPGJ7Ih+XHu63ENupb/Lb2uoTv8s5h8RVeORqcU05IxmWR69GvCT19tx+Fwn/2azDJ2m4LFYqBBiC9XXN+raF9ouD8TL+taI7ZXBKNRps8A9yrm9p3CadM+lCOH/rsHJpNMyzYhdOrWqKbN1CnEmW9lw93vuTTvNQ3fqBAGzX6Qxpf0LXZc7qkkNt3zPoq1+HrLxrtnceynfzj9725QNcwhgVjCggkf1Jkuj1xBUFvvTSjOF4QQ9Hv3btbe+GaxdQ/Zx0zft7yzplIb6B2vzmHT2hP88OVWCvLsgGDIyFY0bdmAud9sx3aOqJgQ0LNfU5q3akjT5sH06Nuk1lsGVhWnQ+GfZUdYuzIGDY2hF7Vh1Nh2GI31XxqhvrJy8jMkrNhezJEbfM2MX/c+IT3+W8PZ93+/sv3pLz3quSCJ/+QAhMAU7M9lR7/HHOyd3P7zlbglm9n5/BxyjiUQ3KUlvV+9hYjBXWrbrFIpreOVPsM/hwFDW9BvcHNysq34+BgxmQ2sWhbtscgJIKpJEFNmdKtZI6sRg1Hm4ks7cPGlF1ZcNys6lh3PfUPSur34RobQ7cmraTFtaG2bRW5sspuzB1d4Z+/bcxnxw9NF21SHs5g2TjHOXpvSNBSbnaPfr6DTzKnVYfZ5Q5Nx/WkyzpM0WP2kfk9HqwlJEgQF+xT1i+3Rt4lHh280yjXaLSo328bBvadJSsypsTFrC2e+1SVSVQNkHYnjz753c2LevxQkpJG2PZq117/O/lnza2T80sg7mVRM/74IVSP7cPH2lM0mDSq3xIOSbyPzQNkyHDrnF/oMvxw0aOjLlTf15udvtqMqrgVbg0Hi4okdaN6qYbWPr2kac+fsYMWiQxiNMk6nSpt2odz35IgSlTGzMgvIyrTSKDKg3I3O6wJ5cSmsvektktbsRtMgtG97hn79GEHtSq4griq7XvrWVWh01izYmW9jx7Nf0/6OiRgsFe+f4C2COjbzGKIRRgPh50g6BHdsTueHL2f/u/M8NlM5G4OfhdA+7b1qq07dp/54gnKSlJjNwb1J+Pmb6N67sdec3ejx7enaM4qtG06iKCq9+jWlaYvqa6N3Nmv/Oco/S6JxOtSiBiZHDqXw+fsbuP/JEcWOtRY4+PR/69mzMx6DQUZTNaZe3Z1xk+uGPGtpqA4ni4bcR358apGAV8qmgywafB+XH/uh2lrvJa/f71kfXkDuidMEd6icTLc3sIQE0f7OiRz69E/UguIx/A53T2L36z9wfO5qDL4WOt49iV4v3oR/swg23j3Lo0wCgDDImBsG0OrKkTX1Meoc2THxWFMyadCtVZ3trlYdnDcOX9M0fvxyG6uWHUFIrrCMJASPvjiaVm29I8wZERnApdNrfsFm6R8H3XR5nE6VPTviyc+zF5vlf/7+BvbujC/2cFjw4y7CI/zp7SEzpzY5+sNKdr44h/y4VILaN6XZ5MHYMnKKO19NQ7HaOfbzKtrfNqFa7PBvHlHURvBsVLsTn/DgahmzIrS9eRxHvl6KanW48oAlifZ3XMrqGS+TfSS+KL6fsfcYif/uJi8upURnbwjwpfmUwfR963YMvvWrN4Q3KEjO4O8pz5K++xiSUUZ1KvR+7RY63ze9tk2rEc4bh797ezz/rohxS5383yurmPXVdKR6nD2Tl+v59VwSgoJ8R5HDz8u1sWtbXJGjP4PdprBowf465fAPf/4Xmx/8uKiSMX33UTIOnPCoFunMs5IdE19ttnR76mpSth4qVlUpW0w0mzqkUgJwznwrp//djZBlGg3vhmyufEhIVRRWjHsCR9ZZ9SGqyv735iPJUrHFXGeelWM//I1PI89hRmOAL+PXvldntNlrg7+nPkfq9mg0h1LUpnLHU18R3LE5jceUrEMFoDoVTv2+jpN/rMfcIIB2t46vd/fyvHH4q5cdcZsFA9jtCjHRqbTrWL6G33WRzt0j2fjvcTcpB18/Ew1C/gtz5ObYkGXJzeEDtVYpG3sigwU/7ubYkVRCwv2YfHk3uvWKZPvTX7mVrWsOxZU+eA4Gfx9CelWfrEPjMX0Y+NH9bHl4NqrVjqqotLh8OIM+ebDC1zqxYC1rb3ijqPBJCMGoBS9WumNU8ob9OLLdiwE1uxNPc3ghS/g1DSMvNtld115RCGxTsy066xI5xxJI3xnj+j07C2e+lf3/N6/I4asOJ0e/X8nRH/92idfdNoGoS/qyfOzjpG455GrlKUlEf7mE/rPuoeXlw0lYsR0kicYX98HoX3dDROeNw/ckIwyuXHlPcgH1ielX92D3trii7lZCuDKEbrp7QLEetiFh/h7rACQJOnSp2eYvAKdOZPDK40ux210Cc5kZBXz49r9ce01XHKU09JDMxqKFSslkwKdRQ5pPHVKttra94RJaXzOa/PhUzA0DKrVekBubzJrrXnNrYrJy8rPMiP25Unr2jqw81y+xJwRu+vVCkmh78zjSdx/FmWstStM0+Fno/ux1F2QY5wzW1Gwkk8EtxRWg4HQ64HooLrvkcVK3Hirq0Zz4z04ihnb9z9kDqCpKgY2N98xi8/0foqkaqt0BGgS2b8qwOU/UScmK+hvnOIdBI1pi9rBAq2kabevx7B4gJMyPV9+fxCWTOtK6XSgDhrbkmTfGukkuGAwS19zcu1iLQkkSWHyMTL2y5msFfv1uB7ZCZ38Gu03hl18OIJfgeILaN6XjPZOxhAVjDgmk7U3jmLjpQ2RTyf10vYVkkPFvHlHpxeFjP6z0qMWEpnHyt3WVumb4kK4eW+rJPiaP7RYVh5OWV45k0rZPaDFjOD6RDWnYsw1DvnyUbo9dWSkbzhcadG3pcXFeMhtpMt6Vax/71yZSt53l2HGFyuKXbyu27Qyu0JDdNUEp/NFnH45lyciHSN97rHo+SBU4b2b4A4e1ZMPqY8QcTsVmdSLLEpIsikTM6jvBDXyKyTaUxJCL2tAwzI+/5u8nLSWPDl0imHhZF0LDa76i8viRNI8dlPLy7LSeOZ2Y934p9kck+5rp/eotNJ8yhG5PXE3qtsP4NGqIqYR+uXUNe1aexxRK1angyPasVFkW5mB/+rxxG9ue+sL15qBpGPwsBHdqjjU1i9zjxRebhYDozxfRaeZURvzwTKXGPF8xFMoibHn0k6JwomQ2YgkJpPODlwGuylpnrrtjF5Lw/DAvAcVqY/er3zPy5+e8Y7yXOG8cvixLPPLcRezZkcDu7XH4B1oYOqo14Y3qh7PwJp26RdKpW/marFQnDRr6kpPtvuCsaXAgrA39XriBPa//iCMzD5/IhvR58zaaTR7M9me/Yv+7vyKZjWhOhYBWUVy89A18I8vXhKW2aDK2Hwc//N1tJigkQdTFpS8Ilkan+6YR2rc9hz75E1t6Ni2mDSNiWFd+73qr27FKgZ3ozxbpFbQl0OGuSQR1aMr+/80jPyGNJuP70+m+aVhCgwCwhAYhjAY0R/G3KslkRJMUj29bHtEgfWeMt82vMrqWjk61sXXDST58a43HfUajxCc/XYUsC1S7A8lkRAhRtOh5ttMUskRo3/ZcuqFiTdMyD54k5tvlOHLyaTZxEFEX96nWhuqaprHqipeIX7qlyH6Dn4W2N431uiJl9tEEfu92q8cCq4A2jbks+luvjnehkB0Tz+/db3O7r6YGAXS6fxp73/gJYZSLfo9UuwPF6kG7CGg2ZTAXLXip2m0+F11LR6faOHU8nZ++3k7M4RT8A8yMm9yJMZd2QAhB30HNMRolHB6yhlRVw25z4utnKpa2eOC9eW4zZE1RSd91lNyTSeXu7Rr91RI23fuBS1/GqRAzZzlRY3ozat4LCKl6lq6EEIyc+ywnf1/PsR9XIhkNtLnhEjdVS28Q0CoSS1gQeaeSi22XLSZaXXXhFlRVlcA2jRn27ROsvekthCSKQmij/3yN0N7taH/7pZxetQtjoC+Ro3ux6e5ZxHy3wq3uQfY10/3pa2vpU5SMPsPXqTSn47N57uFFxfTzTWaZUWPbcdVNrgnGuy//zZ4dCW6x/LAIf97+ZIrbjPu3Ljd71HgxBPgwYc0sGnYvO+/ZlpnL3KjL3bIxDP4Whn33FM0nDy7vR6zTJG3Yz/Kxj6M5FRSrHYO/D/4tIrh0/QfFFp41TSNuyRZXaz5No811Y2gyYQBKgY1jP68iad1eAts2od3NY/GJqH6pkPqA02onecN+ZIuJsP4dkGTP64CaphG/bCvbHv+MzEOn0BwKwZ2aM+CDeyudiltV9Bm+TrWwcN5et5RXu03h7yXRTL6iG75+Jq68sTfRB5Kx2xRU1dU0xmiSueHO/h7DK80mDyb7aILb4qckywR3Kp9QXeLfOzym3zlzrRyfu+q8cfgRgzozPfpbYuYsI/fEaRoN707zaUPdMprW3/4ux39eVfTmFLd4M00nDiRl00GsKZk486zIFhN73/iJsf+8S2jvdrXxceoUBouJqFFlO2whBE3G9qPJ2H6uxkiKWm4Bu9rgvEnL1Kl5jh9JcysGA1d66BlFz8ZNg3n5f5cybHRrIiIDCAy2IEmC7z7bUig7Xfz8Lg9fjk9EA2QfV5hHSBKyr5mBsx9AMpZvfiKXJHYmBAbf86sZt2+jhnR7/CoGzX6QVleOcnP2qTuiOfbTP25phsd//Ze8uJSi7YrVjiMnnzXXv1Gj9p9PCCHqtLMHfYavUwUimwSSGJ/lpobgdCiEhvsVfR/eKIBxUzqzcc0JVzW0BtaCHH78ajvpqXlMv+a/mZS5YSBTdn/O4c8WEbd0C/7Nwul03zRCepa/0jbyol4ei5UMPiba3jTObbumqsR8t4JDsxeiFNhoOWMkne6bVqcrJstLwvLtnjNLFNVTxiw5xxIoSM7AJ7xmhAErQ3ZMPIc+WUjuiSQiL+pFm+vHXFACaFVBd/g6lWbiZV3ZuzPBrSVkn0HNCAgsXlj157y9OOzOYrF8u83Jkj8OMn5aF3x8/puZmoL86froDLo+OqNSdhksJkb/8QorJz7lGk7V0JwKXR670mO3onW3vsOJX/8tmu1mH4nn+NxVTNzycZV0cOoCxgAfJKMB5VwxNQ9VugBoGlINFLmdwZqaxaFPFpK8YT/BnZrTceZUAlqU3E4zfvk2/pn2HIrDieZQiFu6lf3v/sLErbMx15N6jdpED+mUQmpyLvt3J5Ke6q5logMt24Rw/5MjiIgMQJIEJrPMiIvbcss9A92OPXo4FU/NmAyyRHI1NHRpNKwbMxJ+Zcjnj9B/1kymRX9Lz+eudzsuKzqW43NXFQt5KFY7OccSOTHPc0ppfaLlFSNczv0chCy7hb6ELBE+uEuNtT3MPZnEgo43sue1H4lfupWDH/zO711vIXnTAQqS0jm9dg/5iWlFx2uqypob3sCZbyvSw1HyreTFp7L37bk1YnNlsaZlcWLev8Qt2Yxi95zGWRNcEDP84zFp/PLtDk4eS6dBiC9TZnSj76CSFwDtdoXZ765l744EDEYJh0Oh78Dm3HrfIAwG/Rl5Nl16RPHW7CnYrA6MRrlEVdJGjQNJTMh2m1U6nEoxAThvYvTzoeUVI0jZfJDVV75M2o4jWEIC6fLoDDrdNw0hBMkb9ntM03TmWUlYuZ3W14yuFttqCktYMKN+fZ5VM152pRkCmqox7NsniP5iMYmrdyEQCFlgCW/A8O+erDHbtj7+GbaMXM7MBFSHE9XhZPn4J1AK7MgWE6rVTrOpQxj6zePkHj+N00MXNNXm4MS8NfR5zb0QrS5w4MPf2PbYZ641KOF62F68+HXC+nescVvOe4d/PCaN155eVhR2yMu189ms9eTm2Bh5iedshLlztrN3RwIOh1Ikt7x90ynCG/kz7eoeNWV6vcJsKT0McOn0LuzfnVgs/GM0yfTu35TAoIoLemUdiSNtWzR+zcIJH9S5xIKq9N1HWXrRwzgLS+nzE9LY8fRXFCRl0Oe1W/Fp1NCjw5dMBvya1m8NpjM0Gdefq5Lmc3r1LjQNIkf2wOBjpvmUIaTtiiFtezT+zSOIHNWz2moUPJGwfBueXvscma436jOZWqf+2MCOZ76i0/3TPDeqwRW6qouk7ohm2xOfo1jtxbLGlo9/kisTf60RjaizOe+nq/O+31nMyYArdfDX73aiePjl0TSNNR509e12V7qhTuVo0z6Mex4ZRsNQXwwGCaNJZsjIVtxy7yAATidk8/4bq7n72rk8cudv/L3ksFsGD7jUDFdf/Qp/dL+NDXf+H8vHPcFvXW4mv1Dt8Fx2vfwdznPUK535Vg7MWoAjt4Co0b1dzuKcB4YwyLS7ZbyXPn3tY/Ax02Rcf5qO74/B579MpZAebWh3y3iiRveuUWcPrirk8qAU2Dj0yZ/4NQ6jQffWRdLTZ1+nrkpJHPlysatxzTloikLCyh01bs95P8M/cdSzI7DbFXKyrAQ3LB5O0FQNu8OznLK1oPZib+cDPfo2oXufxuTl2jFbDBiNrhS2tJQ8XnhkMdYCB5rmegv7+ZvtnE7I5ppbilepHvzgN04t3FA4Y3Jtyz4Sz5prX2PsynfcxkzbecRjUxXJIJN7MokGnVswdtX/8c+058k5loiQJQy+ZoZ992S5q3p1KkeHuyax+7Uf3PoieMKZ55J6HvXr8yy96GHyE9MRQqA6nLS6ahRtbri4BiyuOPas/CKJ6rPRNM1jeKq6Oe8dfkiYH7k57r9QAvD1d8/JlmSJFq0aenxQ1HeZ5bqAEAL/gOL3fckfB7Db3GWUVy09wuTLu+Ef+N/xh2YvdG+c4lRIWrcPW3q2W4eq4I7N3RQlwRUv9mvian0Z1LYJU/d+SfbRBJQCG0Edm5VYWanjPbo+diUZe49x6o8NSCYDqlNByBLOHHdHGNKzDUKS8GsSxrRDc0hev4/8hDRC+3UoNauntmk+dQin/ljvLhfiUIgc2aPG7TnvQzpTr+xWTB8e/iv/L0k2+fo7+mM2G4qai8iywOJj4JpbKq94qFMyRw4moygeCriMEglxWcW2OUuYDQpJ4PQgJNbj2euQzym2kn3NtL15rFtDksDWUTTo0lJ39jWEZJAZ8dOzTN3/FUPnPMGlGz9k/Or/YfD3KdL6F7KEwc/CgA/vKzpPCEHEkK60vGJEnXb24BJQCx/U+b/wlSSQfc30euVmLGHBNW7PBaGls/bvGH7+ZgdWqwNJEowa244rru/lsTvUGZISs1n6x0FOncigZZsQxk7qWKamfGZGAUsXHuDA7tOEhPkxbkqnam+tqCoqf/22n+ULD5KfZ6dF6xCuubUvrdt5p3F7TfDJ/61j09rjbpEXo1HmzY8nExL2XxHXxpnvE/35ItRz5GsDWkUy/ch3Hhdv45dvY9P9H5IdHYfR30LHe6fS84Ub63xV5IVKdkw8e9/5hbTt0TTs3pquj84gqH3T2jar0qiKwqnf1nF83hpMQX60u2V8qd2wHLkFKAU2zKFBlVJ3LU1L54Jw+OByjLk5Nnz9TBiM3v9Dz0jP59kH/qIg34HTqYJwFSHdeNcABo9o5fXxzvDdZ1tY83dM8eIns8wL74yncdPgahvXm5w6ns7LTywtnsFjlOjUPZKHnhlV7FhrSiYL+96FLTULZ74NyWRAMhq4eMkbRAzpWuo4qsOJMMjVKpFc06gOJ9bULCyhQeWWntCpGo6cfPa9+wvHfl6FbDHR/o6JtL99QpXfDK1pWay98S0SVmwDBP7NIxjy9WNEDOpcoevoDr8GmPPJZv5dccQtNOHrZ+KDOZdXS/5+Xq6N+2+a75ZRJCTBgCEtuPOh6u0D60327kzgm9mbyUzPRwjoN7gFN9zZz2O6pyMnn5jvlnN69W4C2zah/e2XVmiBNSs6loMf/UHO0XgajehB+9smVKrfbG2iaRp7XvuBPW/+jKYoSAYD3Z66mq6PXem1B5rqVNj3zi8c/PgPnLkFNL6kL33euO2CXsxW7A4W9rmTnJiEojRLg6+ZJhMGMHLuf92trKlZZEXHEdCyUbka92iaxsI+d5K570Sxt1eDn4Upe7+sUOhKV8usAfbtTPAYh1YUleTEHKKaBnl9zOTTuUWFYWejqRonjqWVcFbdpGvPKN75dAp5OXZMFkOpbSmNAb50vHsKHe+eUuFx4pdv4+9pz6HaXTr5iat2c2DWAiZt/6RO68ecy/735rHn9Z9w5heKn2Fn9yvfF96byV4ZY831r7syogrXTY7/+i8JK7cz7eA3RR2iLjROzl9L7onTxXLqnfk2Yv/aRMb+EwR1aMqmez8g5ptlSGYjqtVO08mDGTbn8VJlOtK2R5MdHecWqlQdTg7NXkjfN2/3iv1emXYKIcYKIQ4LIWKEEE942C+EEO8X7t8jhCi7OWs9I6CE4iFFUfEPqB49lrBwf5weUkiFgKbN64/zOoMQAv9Ac7X0INY0jV2v/cDycU+g5NuKGlYoBTasyZnsevk7r49Znex94z9nfwZnnpXdr/7glevnHE/k1O/ri2dEqSrOPCuHZi/0yhj1kcRVOz32vKWwanv/u78S8+1yl/poVh6KzUHsnxvY+uinpV435/hpt/oCANXuJOtwrLfMr7rDF0LIwEfAOKATcJUQotM5h40D2hb+ux2YXdVx6xrjp3bGbC7+wmQwSHToEkFgcPVUAfoHmhk0opWbgzSaZCZe5i4SVpcpKHBgt3uuf6gIjtwCsmPicZ6jhb/71R/Y88oPHnPyVYeTU7+vZ8/rP7LsksfYOHOWV//IvEV+Yhq7X/2etTe+iTUly+Mx1uQMr4yVvueYRxE1xWoneeN+r4xRH/FvHoFkdr8vkizhGxXC/lnz3dKGlQI70V8u8ZiPf4aQXm09qprKPmYihnjvb9kbIZ1+QIymaccAhBA/A5OBA2cdMxn4VnMtGGwSQgQLISI1TUv0wvh1gj4Dm5EYl8XCX/ciGyScTpU27UK5++Gh1TruDXf2JzDIwopFh7EWOGjaPJhrb+9Hs5b1o3PR8Zg0vvxwAwmxWSAEPfs14ea7B+DnoUaiNFSnwpaHPib6i8WFKX0a3Z68hm5PXIWmqux7ey6KteQCn4LT6ex65TuUAjuJq3Zx5JtljP79ZaJG967wZ0reuJ997/5K3qlkIkf3ovMD06scLkredIBlFz+G6lRQrXbXa5yHh1dQB+9kswS0ikR1ujsgYTQQ3LF8jWjqOs58Kzue/4aYOctRHU6aTRpE37duL7XrV9ubxrLnjZ+KN+iRBMYAHxpf0hd7pmehRdXmQLE7MZTQqyGwdRTNpgwuFkITBtmV1XPrhMp/yHOo8qKtEOIyYKymabcWfn8d0F/TtJlnHfMX8IamaesKv/8beFzTNLcVWSHE7bjeAmjWrFnvkyfd293VZQry7cSdyiS4gQ9hETUr16qqWlHtQH0gPTWPJ2YuLNYi0WCQaNqiAc+/Pa5Ci49bH/+Mgx/9Xmx2ZfC10P/9e2g+dSg/R17mWRce1x+WpqhuDtSvaRiXn/ipQnYc/XEl62//P5QCu0tq2GzEFOTH5F2f49uocg9hTdOY3+56co4mlHqc7GPmot9eovHF3qkXWTTkPlK3RaOepe5o8LMwZc8XBLSM9MoYtYWmaSwe/gBp26KL4vHCIOPTqCHTD32Dwbdk2YfTa/ew5prXsKXnoKkqQe2bMnLeCwS2jmLpmEdI/Hun2znBnZozdd9XpdqkOhX2vzePQx8vxJlnpemlA+j18k34RlUsxbq0RVtvxPA9/TWc+xQpzzGujZr2maZpfTRN6xMWFlZl42oaH18TbTuE17izB+qVswf4e0k0irP4a67TqZIQm1WiJIYnVEXh0Md/uL1KO/Ot7HntR0xBfhgDS1DkFALJZPA4W7amZJEfn1p+OxxONs38wGVH4fVUmwN7Ri57Xqt8bD0/IbVEOySTAXNIIOGDuzBm0Wtec/YAYxa9RrMpg5BMRiSjq8XkxcveqvfOHiBl80HSd8YUW3zVnAr2jByO/byq1HMbDe3G5Sd/YtLOT5l26Bsm7/yMwNZRAPR7967ihWOShMHXwsCP7i/TJskg0/WRGVx+7AeuSprPkC8frbCzLwtvhHTigLPfI5sA505FynOMzgVGQlymq2bhHIQEKUm5tGzzXzqbw6GQnWklIMjitmahFNhRbJ51jgqSMxCSRO9Xb2Hzgx8XeyhIJgPDvn2SnS98Q9Yh95i9pmnlFvgCyD4Sh3puoxFcD4K4pVvLfZ1zkc0mNA+tJAH8mzdi+uE5lb52aZiC/Bn583M4rXZUm73epa6WRvquox7vqTPPSsqWQ7S72b0z2tkIIQhq28Rte8NurZm88zP2vvUzqVsPE9y5Od0ev4oGXVp6zfaq4A2HvxVoK4RoCcQDVwJXn3PMQmBmYXy/P5B1PsXvdSpHmw7h7N2Z6NYIXVE0mrVwxbw1TWPhL3tZ9Nt+NE1DILhkUgemXtWj6I3G4GfBN7IhebEpbmOcaY3Y/rZLMfj7suuFOeTHpxLUqRl937ydyJE9saVns+WRT4o/DIwGIkf0qFAXJVPDQLe0ujNYwiqfxmgJDSK0b3tSNh0oJg8s+5ppf8ellb5ueTFYTFBSn+B6SmCbKI9ZMbKvmeCOzap27dZRDP70oSpdo7qockhH0zQnMBNYBhwEftE0bb8Q4k4hxJ2Fhy0GjgExwOfA3VUdV6f+M2JMGyw+Bs5W5TWZZLr2jKJRY5cI2srFh1m0YD82qxO7TcFmc7J04UEW//5fpogQgn7vzSyumVPYsLzv23cWbWp91SimH57DdbmLmLRlNpEjXb10299+Ka2vGY1sMWEM9MPgZ6FBt1YM+75izUB8GzWk0dBurhDRWRj8LHR9pOx2jY7cAjIPnMCe7b7wN/zHp/FrFoExwBeDnwXZx0zjS/rS6b5pFbKxPFhTMoldtInUbZ4lqs8HIkf1xLdxaFHoBQAhkE1G2lxfN5U3vYFeaatTq6Sl5PHLdzvYsy0ek8XAqEvaMWF6l6LK5Ptvmkdmhrt6op+/iY+/L+5EE1fvYtdL35F9JI6Q3u3o+cINhPRoU25b8uJSSNt5BP9mETTs3rpSn8eWns3fU54ldfsRlwKkzUH3p6+h+9PXlniOpmlsf/JzDnzwO8IgoTkU2t4yjv7v3VOsXF9TVRL/2UnuqWTC+nWoljDB9ue+Yv87vyKZjGiqil+TMC5Z/hZ+Terfetq5qIpCwvJtpO85RmDbJoT178DGu2cRt3QLqBqhfdsz5MtH630Wki6toFNvuWna96glxK+/XnBtnV2ozj6aQEFiGg26tiwz9r3rle/Z/cr3xbNhfM10fuhyer10U3WbWsTJP9az5trXikn5ClmiQbdWTN5ecuGQLT2bxNW7Mfr7EDmyR53U9LFl5rJk+APkHHdVyco+JswNApiw/n0soUFoqlasMUxJaJrGsR9WsvedX7CmZtF4dG96vnhjnZKb0KUVdOotjZsFE3vCvZioUVRAnXX24IrjnsncKI197/7Czue+dtvuzLdx4P0F9HzxxhoTezswa4G7bruiknUoluyYeALbNHY/50y/VpMBNNdC+MVL3iC0T/sq2ZKx7zgHP/qDvNgkGo/tR9sbx2L0r3wB4/YnvyDrcFzRQ9WZU4CSb2P9be9y8eI3ym3Tlodnc3rNnqI8/KM/rOTUXxuZuucLr2fUVAfnvR6+Tv3m6pt7u2XlmMwyV5/TCas+krRuLzue/6bE/Y6cghJ7uFYHtvRsj9slg4w9y31dIXXbYbY97urX6sjOx5GTjy0tm+Xjnihx8bo8nJi/hj/730P0F4uIW7yF7U98zh+97sCelVvpax7/+Z9ib1DgepglrNxRpq2aprH2prdY2O9uElZsL1Z0pSkqztwC9r37a6Vtq0l0h69Tp+nULZLHXhpNp26NCAy20L5zBA8/dxHde7vPNusbB2cvdBVolUBQ+yY1qtnffOoQj7IBCGjQ1X294PAXi1Fs7varDieJ/7gXH5UH1eFk/W3vohTYih52znwb+XEp7J+1oFLXBEpefNa0Mhemj/+ymhPz/nVVOHuy2e7k9L+7K21bTaI7fJ06T9sO4Tz+0hg++OZy7n18GEphcVZ9x56R47HgC0AyG+g/a6bHfdVFp/un49c4FLkwli0kCdnXzKBPHkT2oKtjz8wFT+srGtiz80sdS9M0Yr5bwW9db+GniGn8c/kLZB2OJWPfcY9vNYrVzsn5ayr3wYDm04e6rS0ISaLRiO4eP9vZRH++yC3UVfxCgoBW9aMYTY/h69QLNE1j3vc7WbbwEAajhKKoNG3egAefGUlAYPmLo+oSLaYPI2ntXjdnIiSJMYveIGpUzxq1xxzsz+SdnxH95WJiF2/Gr0kYne6dWlTLcC4tpg0lbtEmN/sVu6PMfq27X/mOvW/OLVL8PPnbOhJWbOei317yWLwGYAqufOFX37fuIGnNXgqSM3DmFGDw98HoZ2Hw54+UeW5ZIR/ZYqLLo2Wn3dYF9CwdnXrBxjXH+fqjTdhs//3xybKgfecIHn9pTC1aVnkUm53Fwx4g88BJl9OUBLLFRN+37vCapv3Z5CeksvnBj4n9ayNClmk5YwT93rmz0hW0qlNh+SWPkbLlUDH7e718ExGDu7LloY9J3R6NJSSQLg9fQacHpiOEwJFbwE8R01HO6UEsZIk2N15C2o4jZOw5Vmymb/CzMPTrx2hx2fBKf37V4eTk7+tJ332UoHZNaHHZsFI1c84Q/eViNt3/EUq++yzfEh7MwI8foMW06hVJrAh6WqZOvef5RxZzIsa9qYvBKPG/z6dVmwR1daPY7Bz76R9O/rYOc2ggHe6YVGq/08riLLAxv/31FJzOKOoFIJmMBHVoyuQdnyKkykV3VafCyQVrOT7vX0xBfrS/dQKyr5lFA+8tptdv8DXT4e7J9H3rDtJ2HmHJyIdweAj7BLVvysXL32LZmEfJT0hDSALF5qDTfdPo88ZttdKeUnU4WT7uCdeDLbfAtc4hCQbPfpDW146u9L2rLvS0TJ16T16OZ2ljWZbIz3PUW4cvm020vXEsbW8cW63jHP9lNfbM3CJnD6DaHeQcSyRx1S6iLqpcTyLJINPyihG0vGJE0bZVM17CaT1XyM7GwQ9/p8ez1+HbOLRE7aOA1lH4Nw1n2sFvSNl8kILT6YQN6FRppVFvIBkNXLL8LeKXbyNh5XZ8whvQ+trR9SIN81x0h69TL+jeO4pVy2JQzlnQMxplwhvVvKhX6rbDbH7wY1K3HcYc7E+nBy+j6yNX1LnZ3hnSdx/12KlJdTjJ2He80g7fE2k7j3hczJVMBnJOnCa4Y3N8IhqQdyq5+H4fE92edMlwCSEIH3BuH6XaQ0gSTcb2o8nYfrVtSpWom7+dOjrnMPHybvgFmDAYXb+yQrjy8W+6uz+SBxGs6iTz4EmWjHyI5PX7UG0OCpIy2PXSt2x+8OMataMiNOjU3KPyp2QyENTeO01TzhDcqYXrB3QOqt2JX9Nw9r71s8eOXeEDOhExuH51aqtv6A5fp14Q3MCH19+fxMTpXWjXMYxBw1vyzOtj6TOw5nVPdr/2QzEddQAl30b054uwZeTUuD3loeWVozD4WYq9gQijjG9kCFFjKt7VqzS6P30Nsk9xdU3Z10zr68dgDvZ3NaopcA/RJW/YX2KGjo530B2+Tr3BP9DMlCu78/TrY7n9gSE0b1U7cd30nTEec8Ulk4GcY95X/c4/nU5ubHKVlCuN/j5cuukjosb0RsgSwiDTfPJgJqx7v5hAmzcI69uB0b+/7HpzEAKDvw+d7pvGwA9dTUAcOe5ieOBqQHJuNaw3yY1NZv9789n71s9kHjpVbePUZfQYvk69xm5z8uv3O1mz8igOu5OOXRtx3W39iuSVSyLnWAJbHvmEhJU7MPi4dOW7P3NtmUU4AMGdW7gcxjlxatXu9KqIVs7xRFZf+TLpe44hJIFf4zCG/fAUYX0rl8UT0KIRFy95o6iZdnWuN0SN7s20g9+gOpwIg1wsuyZyRHdiF212KzoL7tS8XGmSleHInGVsvOs910NT1dj54hw6P3w5vV+6uVrGq6voaZk69Zq3X1jJ4f1JOByFTkyAj6+RNz+aXGLmjjUlkwUdb3JlrRQ6P9nHTOOxfblo/otljpm2K4ZFQ+4r3jDFYiK4QzNAw9QggE73TqXZ5MGVTiNUHU5+bXUN+YlpxR4sxgBfLov5DktYcKWuWxfIio7lz/73oBTYUe0OhEFGNhu5eNlbRAzq7PXxCpIz+LXF1W5hONnHzPi17xHaq53Xx6xNqrunrY5OrRB3KpPoA8lFzh5ck0aHXWHVsiMlnnfo0z9x5luLnD2AUmAjfukWso7ElTluSI82jPnrNYI7NXc1zfA1Y7CYyDp0ivRdRzm9ahdrrnudHR5UMMv92ZZuceWpn/sW4XQS8+3ySl+3LhDUrinT9n9Fp/unETGsG+1vn8DknZ9Vi7MHiP1rk8fuVorNzvG5q6tlzLqKHtLRqbckxmUhye4zaIdD5ZiHIq0zpGw66DbbA1e+dcbe4x57lZ5L5IgeTN33FapT4eCHv7H9ma+KXdOZZ2X/u7/S+b5plZqN58WmoDrdS/qVAjs5J06jqSq2tGyMQX5FYajYxZvZ8/qP5MelEDG0Kz2ev6FcEs21gW9UKH3fvL1S56qKwu7XfuTArPnYM3MJ6dmW/rNmVu6BUXcDHNWCPsPXqZdomoaPnwlVcf+LFQKOx6Qy/8dd5Ga7Z4M06NLSrQ0huKpGA9tWTIVTMsjELd1SLLxTtM9kIGXzQY/n5RxP5MicZZz6cwOKh4XKsH4dPKY2Gvx9QIOfG1/B3GZX8kPDyWx+8CMOzl7I6iteJHn9PnJPJnH0x39Y2PsOso8mVOjz1Ac23/che9/8CXt6DqgaadujWX7xo6TvPebx+KaXDvC4yC5bTLScMaKara1b6A5fp96xb1cCD922gPdeWYXdrrj5RU2DrAwrS37bzzMP/Onm9DvcMxnpnMVZyWwkpFdbGnZtVWF7/BqHeVwA1VQNS0SDc2zT2PzAR/zW+WY23fs+a657nblNZrg5q9A+7Ykc3r1Yn17JbMTcMIAjXy/FmpSBanOg5Ns49NlfbHnwI5xnP3RUFWeelV0vfVvhz1OXsWXkcOTrpW4PWKfVzu5Xf/B4jk94AwZ+fD+yxeSSRSjMUgps24SMfcdxliB7fD6iO3ydekVCbBazXl9Nemo+DocrZ7ukt3KHQyUnx8bShQeKbfdvGs64Vf9HSK+2CFlCMhtpcdkwxvz1WqVs6njvVCRL8QeIkCV8G4e6dX469cd6or9cjGK148y14sjOx5aaxcqJT7ulXV70+8v0fPFGAts1wb9FBJ0fvAyfRg3dctjVAjuq3T38oykqp9fsqdRnqqvknjjt8e0MVSNj99ESz2t741imHZ5D+zsmIskyQpbI2H2UTTPf5/eut9TZ+glvo8fwdeoVy/86iNNxzuu5BrJBYDDI2KzFHZ/TobJ7ezyXXVtcaji0dzsmbfsEZ4ENyWioUqORkB5tGPLFI2y46z1QNVSnQlD7Jlz0xytuWTqHP/3To7a6LT2HtB1HCO39X8aIZDTQ9eEr6PrwFUXbfm58eYVs82tc//ReSsO/RSPPOjySoEH30t/O0nYc4fDshcXkjp15VvJiU9j18nf0/7+7vW1unUN3+Dr1itMJ2R6bmhsMMorTczvAoAYlC6uVp3F1eWh15SiaTxtKxt7jmIL8PPZ/BXDmeRaBE5LwWH16LqF92hP71yb3ximSQJLlYs5M9jUXadPUdTRN4/S/u4ldtAlTkB+trxlNQMtIFLsDpcCGMdAPIVzyy/4tGpF9OLbY+bLFRPenrinx+qcWbuDfq17xqG2v2h2cmPev7vB1dOoaHbs0IuZQalE45wyKotK4WTBxJzNQzlrINZllxk2uGREu2WQsNkM/F2eBzeMC7RlC+5bd+LvXSzeR+PfOYtLDAAjXmgECDL4WhCzR543baDphQLntry00VWX11a8Qt2gzznwbklFmz+s/EtqvIymbDqApKv7NIxj0yYMc+mQheSeTil9ACAa8fy8Nu7UucYxtj3/mMTPrDLLZVOK+8wk9hq9Trxg1rh0WXwOS9F+oxGSWGTqqNY88N4rmrUMwmWR8fI2YzDKXX9uTzt3rRvu5dbe8TbqHOLNkNjLk68fL5XQadm/NuDX/I2pM7+KxbEVDUxSEQSZqTG+uSl5AhzsnedP8auPUnxtdzj7PCpqGaneiFNhJ+nc3qs2B5lTIOZrAiklPE/vnRo+OO27pllLHyDlWcraSZDHR7rYJVf4c9QF9hl8BrAUO7DYnAUGWWmnEoAMBgRZe+r9L+e2n3ezZHo+Pr5GLJ3ZgxMXtkCTB82+NIykxm+wsK81aNMBsKVsqoSawpWdz8rd1qB7izw17tKHF1CHlvlZor3ZcsuwtvvUd57ZPcyjEL9taLomInOOJrLr8RddDSAiixvRmxE/PYAr0K7ct3uDYj3+X3jO2ELXADp7+7DSNrDK0cfyaRZBTQopq1EW96PLgZeUxtd6jO/xykJ9n58sPN7JraxwICG7gy833DKgzM8cLjYYhvtwyc2CJ+yMiA4mILF1Lp6YpOJ2ObDJ4dPi2lMxKXbMkZUmthLWMs7GmZTG/ww1oZ4XG4pdsYV7ra7kqaX6N6vp7zLopiRJSsnzCG3jeUUjPl25i/W3vFJfDMBno/MgV9HnllvKPX8/RQzrl4L1XV7FraxxOp4rToZKanMt7r60iIdZd01tHxxP+raJKVLsM6tCsUtdsPLavu2SAJNF4bN8yz9366KfFnP0ZbGnZHPzo90rZU1na3jTOo1a/G6U8hPxblT75an3VKAZ+dD++USEgBJbwYPq/dw+9X76wxNN0h18GCXFZHI9Jw3nOrMnpUFn254ESztK5ENA0DUduQbk03A0WE50f8hw2SFq3F2c5MnTOZeCH92EOCSpylgY/Cz5hQQz44N4yz01aW3J+/oH3f6uwLVUhcmQPOtw1CdliQvYxYfD3QRhkV5HUGYRANhuKFaKdQfYxEdan7AXvtjdcwoy4X7jBupSrTs+nw52TLrjQrO7wyyAtJQ/Z4H6bVFXjdPyFUayh40788m3Mb3c9PzSczPdBE9l03welZuAAyBYzwlO+v+ZKG6wwQtD6utEEtmlM2MBO9HrlZqYf+Q7/ZmVLNFtKCYEUJKVX3JYqIISg71t3MHn35/R96w4GfngfVyXPp8+bt+PXPAJjoB9NLx3ApZs/xhIWXPytRggMvhZaXTWq3ONJxgs3kn3hfvJy0rR5sFsKIIDBKNGuc3gtWKRT26RuO8zfU58ryptXnArRXy7BnpnLsG+fLPE8a1JGsSbiZ1AdTmypFQsPpmw9xNKLHkG1O1HtDmQfEzkxCTSfNhSjf9kN3Xu9fDPLRj/icZ9vLRVrBbVtUiRcl3PiNLLJSK+XbqLZ5EFFC8kT1s1i3U1vk7h6F+BKZR369WMYA3xrxeb6hj7DL4Pghr4MHdUak/m/mZkkgcViYPT4sl8jdc4/dr/+o3uLwwIbJ379F2spC7BRo3u7xM/ORQgaDe9eIRvW3/oOztyCog5RSoEdW3o22x7/rFznR43qSXC3lm7bJbORro/MqJAt3mbnC9/wW6eb2PLwbDbeM4u5ja8gfoWrL4Zf4zAuWf4W12b9yTUZf3Dp+g8IaufdnryVIfdUErtf+57ND88mftnWYtLbdQl9hl8Orr+jP02aBbPsz0MU5Nvp0iOKy67tQVAJDTZ0zm+yDp1yr3TF5SxzTyWXKIfceGxfQnu3I2XroaJsEYOfhRbTh9Ggi7vzLQlHTj6ZB93TEDVFJW5J6fnoZzN+9XusnPg0KVsPuzJlnArtb7+Utje7p3vWFEnr97H3nV/cHqj/TH+Bq07PK+qI5a0KaW8Q+9dGVs14GU1RUe0Ooj/7i4ihXRm98NUqSXZUB7rDLweSJBg9oQOjJ1SutZzO+UVon/ZkR8e5Se6qdieBbUrWn5dkmYuXvcmRr5dy9LsVSCYj7W+fQMsrRlRofMlkQEjCY4aianPgtNoxWMou4jIH+zNh7SyyDseSF5tMg26tykxvLA/27Dz2vjWX43NXIZmMdLjjUjrcPblczi9mzjKUAvfCKiEJ4pdvo/mU8tcr1ASKzc6/17xWTBbDmWclae1ejv/8D62vHVOL1rmjh3R0dCpI96euQT5nhmnwtdBx5hRMQf6lniubjHS4YyIT1r3PuH/epdWVoyqc8y6bTTSdNMhjFyfV4WTzAx9W6HpB7ZsSNbp3hZy9pmk4rXa3VFPFZmfRoHvZ9+4v5BxNIOvgSbY99QWrZrxUruuqdqfHtyc0UD2spdU2yRv2eywGc+ZZifl2Rc0bVAZVcvhCiIZCiBVCiCOF/3v8jRFCnBBC7BVC7BJC6E1qdeo1Qe2bMmHtLCJH98LgZ8GvWTi937iVPpXs4FQZBn/6kEeHrykqR79dUWbGUFWI+X4Fc5vM4Hv/CfwYNpV9//u1yPGfmL+W3JNJxQrMlHwb8cu2kr6nZPniM7S4YoTHnHzV4SRqdC/vfQgvIRkNJRaDyXWkyvtsqhrSeQL4W9O0N4QQTxR+/3gJx47UNC21iuPp6NQJGnZvzdjlb9fa+OYGAUgmYwk6+ApKga1c8goV5cT8NWy4839FaxD29By2PvwJJ379l4uXvMHpf3eXKJOQsulgqQJnAE3G9aPppIHELtyIM9/mysc3SAz86H7MDQK8/nmqStjATsgWE46c/GLbDX4W2t4yvpasKpmqOvzJwIjCr+cAqynZ4evoXLDknkxi/6z5pO04QkiPNnR6YDoBLRpV6ZqNhncjbvEWtxCIXzNX7np1sOPZrz22c0zZdJDFwx8kfGAnkCU4Z31DkuVypXsKIRj+/dMkrdnDyT/WYwzwpfW1o8vVZ7g2kGSZi/54meVjH0dTNVfarYDW146h2aRBtW2eG6Kkcu9ynSxEpqZpwWd9n6FpmltYRwhxHMjA9fLzqaZpJeaOCSFuB24HaNasWe+TJ09W2j4dnbpA+p6jLB76AIrVjupwIowGZLOR8WveI6RHm0pfN/PgSf4aMBNngc3laCSXXvzo318manRvL36C//jWf7xHhw8gjDJCSEWpokXbJQmfyIZcfvzHOpe14i0ceQXELtyILT2byFE9Ce7YvNZsEUJs1zStj8d9ZTl8IcRKwNNU5GlgTjkdfpSmaQlCiHBgBXCvpmlryjK8T58+2rZteshfp36zePgDJK3d67Y9fFBnJqx7v0rXzjmeyN635pKy+SBBHZrS9bErq/QQKYs/et7uUeK5NII7t2D0wlcIaKmLDdYEpTn8MkM6mqaNLuXCSUKISE3TEoUQkUByCddIKPw/WQjxG9APKNPh6+icDyRv2F/i9pwTp6sU2gloGcmg2Q+UeowjJ5/MQ6fwjQzBr0lYpccC6PPm7ayY+DSah85RnpBMBtreNFZ39nWEqqZlLgRuKPz6BuCPcw8QQvgJIQLOfA1cDOyr4rg6OvWG0pQg/576XLWOvfu1H/ip0WUsG/Mo89tdz/JxT2DPzqv09Rpf3IeRvzyHOFdfSvIsQiZkGdlc97JVLlSq6vDfAMYIIY4AYwq/RwgRJYRYXHhMBLBOCLEb2AIs0jRtaRXH1dGpN7S//dISHWJ2dBzZMfHVMu7xX1az5/UfUQpsOLLzUax2ElfvYu2Nb1bpus0nD2b64W+JHNUTIUsIg0yj4d2Lq1ueQdNoPn1YlcbT8R5VytLRNC0NuMjD9gRgfOHXx4CKCYXoXPBomsbubfGsXnEEp0Nl4PCWDBjaAtlD7nldp9crN3P4s79wZOe77ZMMcpVm3KWx9525bimSqs1B3JIt2DJyqpTmGNAykrEr30GxOxCShGSQif56CZvued9VHyAEmlNhyFeP4tuoYVU/io6X0KUVdOok33++lbV/H8Vmc8WKow8ksfHf4zz07Khi/WzrA7LJSJeHr2D3qz+4Z7DIEg27tqqWca1JGR63SwYZW3rVHP4Zzs71b3fTOJpdOpDYRZtACJpeOgBLSFCVx9DxHvVvuqRz3pMYn8W/K2OKnD2AzaYQfTCZ/bsTa9GyytPp/mn4Nw8vauAhZAnZ18zgzx+uNn32yNG9PFbjyhYT/s3L1syvDJawYNreOJa2N1yiO/s6iD7D16lzHNhz2mOvapvVye7t8XTtWbJAWV3FFOjHpB2fEjNnOXFLt+DXJIyOd0+ukEpmRen53A2c+n09zlwramFWjexrZsAH955X+fDOAhsx3y4nbtEmfCJD6HDXpGpNTa3P6A5fp87h62dCkt1dvsEg4R9Qd2RxK4rRz4eOd0+m492Ta2Q8/+YRTNn9BXvfnsvp1bvwb9GIro9dScTgLlW+du7JJDIPniSoXRMCWtXeA9iRV8BfA2aSe+I0zjwrQpY4+sNKBn/6EK2vKTGj/IJFd/g6dY5e/ZowZ7a7w5ckwZCR1RPvPl/xaxLGgFkzvXY9xe5gzXWvE/vnRiSzEdXmIGp0L0b88ny5JJm9zaHZC8k5llAkqawpKkq+jQ13v0fz6cNqxaa6jB7D16lzmC1GHnnhIgICzVh8jPj4GDFbDNzx0BBCw0uXH9apXna9MIfYvzahWO04svJQrHYSVu5g22Of1oo9Jxes9ayfLwRp26NrwaK6jT7D16mTtGkfxqyvLyPmUApOp0rbjuGYTOdP3Lm+cujTv4o1+wBQrHaiv1xC/1kzEaJmM6hK6j+gKSrGQL3P7bnoM3ydOossS7TvHEHn7pHnhbMvSEoncfUuck8l1bYplcaZW+Bxu2K1e25cUs10nDnFYyWzYrWz582fyDleP7O6qgvd4evoVAOOnHychTNhVVFYf+f/8UuLq/l76nMs6HAjK6c8W7S/OlGdCqfX7CHh7x04re6hj4oSMbSrx+2hfdtXuHOXN2g6YQBdHr4cyWR0yTIXoikqx39ezcLed5IXl1LjdtVV9JCOjo4XSd97jHU3v0367qMIIYga04uQXu04+v1KVJujqBNUwvJtbL7/QwZ/9nC12ZK8cT8rJz/7X7GXpjF0zhNV6gvbf9ZMFg2+1yX1bP9P6nngR/d7yeqKIwwGNDQ3DX5UFWeelb1vz/XqwnV9pkp6+NWNLo+sU5+wpmYxr+11OLL+k0oQBhk0za3hObgKoK7N/qtacuIdeQXMbXyFm5yD7GNm2oGvq1R4lRubzIH3F5C69bCrmcv902pNDTN1ezSLhz9QokY/uLqTTd5ZYguO844qySPr6OiUjyPfLHVrOag5S268rToVFJsdyeDjdVtiF250azAOrvaHMd+toMcz11b62v5Nw+n39p1VMc9rHP1+hWv9oCSEIKB1/SvUqy70GL6OjpfIOhTrlsECeJQ3AAhs0xijn/edPYAtIwfN6f5Wodqd2NKyqmXM2kB1KiU2EQeQfUx0fXRGzRlUx9Edvo6Olwjr39FjxohkMiD7mRGFmjlCljD4WspsXFIVoi7qhSdPaPC30GRc/2obt6ZpecUIDL6eq68tYUEM+/ZJwvp3rGGr6i66w9fR8RKtrh6FuWGAK25fiGwxETagE9P2fU2HOycS2rcDra8bw8QtH9FoePWphge1b0rbm8YVewAZ/CxEDOlG1Ohe1TZuTRMxpCutr7/YJUonBMIoI1mM9H79Vq5MnEeLaUNr28Q6hb5oq6PjRQqS0tn21Bec+n0DstlI25vG0v3Z62qlxF/TNOIWbeLwF4tR7Q5aXzOaljNGnlfCaWdI2XKIU3+sR/Yx0erKUQS2aVzbJtUaVWpiXpvoDl9HR0enYpTm8PWQjo7OBUL20QTSdh4pkkrWufDQ0zJ1dM5zck8l8ffU58g6FIswSEiyzOAvHtHj2xcgusPX0TmP0TSNZWMeJedYYrHirzXXvU5Q+6Y06Nyi9ozTqXH0kI6OznlMyqYD5Cemu1X6qnYHBz/6vXaM0qk1dIevo3MeU3A6A+Gh6bumqOTFJteCRTq1ie7wdXTOY8IGdEQpFGw7G9nXTJNx/WrBIp3aRHf4OjrnMb6RIXS8d2qxAizZYsIvKpQ2N1xSi5bp1Ab6oq2OznlO3zdvJ6xvBw5+sAB7Vh7Npw+j8/3Tqk3HR6fuojt8HZ3zHCEELS8fTsvLh9e2KTq1jB7S0dHR0blA0B2+jo6OzgWCHtLR0dGpMaypWRz5ZinZMfGED+hEyxkjMfh4ljfW8T66w9fR0akR0ncfZfHwB1AdCkqBjWM//s2ul79j4uaPsYQG1bZ5FwR6SEdHR6dGWHvjmziy84u6gjlzreTHpbLjua9r2bILB93h6+joVDu2jBwyD5x02646nJycv7YWLLow0R2+jo5OtVNa0xXJbKxBSy5sdIevo6NT7RgDfIkY1s2tobvsY6LdzWNryaoLD93h6+jo1AjD5jyOf/MIjAE+yD5mDL4Wwgd1oduTV9e2aRcMVcrSEUJcDrwAdAT6aZrmsR+hEGIsMAuQgS80TXujKuPq6OjUP3yjQpl2eA6Jf+8k98RpGvZsQ1jfDrVt1gVFVdMy9wHTgE9LOkAIIQMfAWOAOGCrEGKhpmkHqji2jo5OPUOSZRpf7LHdqk4NUCWHr2naQXBpdZRCPyBG07Rjhcf+DEwGdIevo6OjU4PURAy/MRB71vdxhds8IoS4XQixTQixLSUlpdqN09HR0blQKHOGL4RYCTTysOtpTdP+KMcYnqb/WkkHa5r2GfAZQJ8+fUo8TkdHR0enYpTp8DVNG13FMeKApmd93wRIqOI1dXR0dHQqSE2EdLYCbYUQLYUQJuBKYGENjKujo6OjcxZC0yofNRFCTAU+AMKATGCXpmmXCCGicKVfji88bjzwHq60zK80TXu1nNdPAc7UY4cCqZU2tubQ7fQuup3eRbfT+9Q1W5trmhbmaUeVHH5NIoTYpmlanc/n0u30Lrqd3kW30/vUJ1v1SlsdHR2dCwTd4evo6OhcINQnh/9ZbRtQTnQ7vYtup3fR7fQ+9cbWehPD19HR0dGpGvVphq+jo6OjUwV0h6+jo6NzgVAnHb4Q4nIhxH4hhCqEKDHdSQhxQgixVwixSwjhUZq5uqmArWOFEIeFEDFCiCdq0sbC8RsKIVYIIY4U/t+ghONq5Z6WdX+Ei/cL9+8RQvSqKdsqaOcIIURW4f3bJYR4rhZs/EoIkSyE2FfC/jpxLwttKcvWunA/mwohVgkhDhb+rd/v4Zg6c09LRdO0OvcPl75+e2A10KeU404AoXXdVlwFZ0eBVoAJ2A10qmE73wKeKPz6CeDNunJPy3N/gPHAElzaTAOAzbXwsy6PnSOAv2rjd/EsG4YBvYB9Jeyv9XtZAVvrwv2MBHoVfh0ARNfF38/y/KuTM3xN0w5qmna4tu0oD+W0tUgiWtM0O3BGIrommQzMKfx6DjClhscvjfLcn8nAt5qLTUCwECKyDtpZ62iatgZIL+WQunAvgXLZWutompaoadqOwq9zgIO4K/7WmXtaGnXS4VcADVguhNguhLi9to0phQpJRFcTEZqmJYLrFxgIL+G42rin5bk/deEelteGgUKI3UKIJUKIzjVjWoWoC/eyItSZ+ymEaAH0BDafs6te3NOqdryqNF6QXQYYrGlaghAiHFghhDhUOGPwKjUtEV1ZSrOzApepkXt6DuW5PzVyD8ugPDbswKVlkluoIfU70La6DasgdeFelpc6cz+FEP7AfOABTdOyz93t4ZQ6d09rzeFrVZddRtO0hML/k4UQv+F65fa6c/KCrTUiEV2anUKIJCFEpKZpiYWvmsklXKNG7uk5lOf+1AWZ7TJtONsRaJq2WAjxsRAiVNO0uiSuVRfuZbmoK/dTCGHE5ex/0DRtgYdD6sU9rbchHSGEnxAi4MzXwMW4euzWReqCRPRC4IbCr28A3N5MavGeluf+LASuL8yGGABknQlR1SBl2imEaCSEq+enEKIfrr+xtBq2syzqwr0sF3XhfhaO/yVwUNO0/yvhsPpxT2t71djTP2AqriemDUgClhVujwIWF37dCleWxG5gP67wSp20VftvFT8aV5ZHjdsKhAB/A0cK/29Yl+6pp/sD3AncWfi1AD4q3L+XUrK3atnOmYX3bjewCRhUCzb+BCQCjsLfzVvq4r0sp6114X4OwRWe2QPsKvw3vq7e09L+6dIKOjo6OhcI9Tako6Ojo6NTMXSHr6Ojo3OBoDt8HR0dnQsE3eHr6OjoXCDoDl9HR0fnAkF3+Do6OjoXCLrD19HR0blA+H94v1QoQheU3AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate the NN model\n",
    "#因为我们想要尽量减少全局变量，所以我们想要用一个空的类，存放nn较多的参数\n",
    "class NN_Model:\n",
    "    epsilon = 0.01               # learning rate\n",
    "    n_epoch = 1000               # iterative number\n",
    "    \n",
    "nn = NN_Model()\n",
    "nn.n_input_dim = x.shape[1]      # input size 二维 所以应该是两个\n",
    "nn.n_output_dim = 2              # output node size\n",
    "nn.n_hide_dim = 8                # hidden node size\n",
    "\n",
    "# initial weight array (random)\n",
    "nn.W1 = np.random.randn(nn.n_input_dim, nn.n_hide_dim) / np.sqrt(nn.n_input_dim)\n",
    "nn.b1 = np.zeros((1, nn.n_hide_dim))\n",
    "nn.W2 = np.random.randn(nn.n_hide_dim, nn.n_output_dim) / np.sqrt(nn.n_hide_dim)\n",
    "nn.b2 = np.zeros((1, nn.n_output_dim))\n",
    "\n",
    "# define sigmod & its derivate function\n",
    "# numpy.exp can be used on array\n",
    "def sigmod(x):\n",
    "    return 1.0/(1+np.exp(-x))\n",
    "\n",
    "# network forward calculation\n",
    "#如果要实现任意层的话，写一个循环即可\n",
    "def forward(n, x):\n",
    "    n.z1 = sigmod(x.dot(n.W1) + n.b1)#变量存到了结构体当中\n",
    "    n.z2 = sigmod(n.z1.dot(n.W2) + n.b2)\n",
    "    return n\n",
    "\n",
    "\n",
    "# use random weight to perdict\n",
    "forward(nn, x)\n",
    "y_pred = np.argmax(nn.z2, axis=1)#取出最大值索引（只要有arg开头都是取下标）\n",
    "\n",
    "# plot data\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y_pred, cmap=plt.cm.Spectral)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "c6ac2156",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch [   0] L = 104.872111, acc = 0.385000\n",
      "epoch [   1] L = 101.588574, acc = 0.550000\n",
      "epoch [   2] L = 99.435219, acc = 0.520000\n",
      "epoch [   3] L = 97.867018, acc = 0.505000\n",
      "epoch [   4] L = 96.553031, acc = 0.505000\n",
      "epoch [   5] L = 95.342019, acc = 0.520000\n",
      "epoch [   6] L = 94.171469, acc = 0.530000\n",
      "epoch [   7] L = 93.015318, acc = 0.575000\n",
      "epoch [   8] L = 91.861637, acc = 0.620000\n",
      "epoch [   9] L = 90.704067, acc = 0.680000\n",
      "epoch [  10] L = 89.538683, acc = 0.705000\n",
      "epoch [  11] L = 88.362861, acc = 0.730000\n",
      "epoch [  12] L = 87.174877, acc = 0.780000\n",
      "epoch [  13] L = 85.973752, acc = 0.810000\n",
      "epoch [  14] L = 84.759182, acc = 0.825000\n",
      "epoch [  15] L = 83.531494, acc = 0.830000\n",
      "epoch [  16] L = 82.291608, acc = 0.850000\n",
      "epoch [  17] L = 81.040998, acc = 0.850000\n",
      "epoch [  18] L = 79.781641, acc = 0.850000\n",
      "epoch [  19] L = 78.515964, acc = 0.855000\n",
      "epoch [  20] L = 77.246786, acc = 0.855000\n",
      "epoch [  21] L = 75.977245, acc = 0.845000\n",
      "epoch [  22] L = 74.710727, acc = 0.840000\n",
      "epoch [  23] L = 73.450787, acc = 0.840000\n",
      "epoch [  24] L = 72.201069, acc = 0.840000\n",
      "epoch [  25] L = 70.965227, acc = 0.840000\n",
      "epoch [  26] L = 69.746844, acc = 0.840000\n",
      "epoch [  27] L = 68.549362, acc = 0.840000\n",
      "epoch [  28] L = 67.376012, acc = 0.835000\n",
      "epoch [  29] L = 66.229761, acc = 0.840000\n",
      "epoch [  30] L = 65.113260, acc = 0.840000\n",
      "epoch [  31] L = 64.028816, acc = 0.840000\n",
      "epoch [  32] L = 62.978363, acc = 0.840000\n",
      "epoch [  33] L = 61.963453, acc = 0.840000\n",
      "epoch [  34] L = 60.985255, acc = 0.840000\n",
      "epoch [  35] L = 60.044567, acc = 0.845000\n",
      "epoch [  36] L = 59.141833, acc = 0.840000\n",
      "epoch [  37] L = 58.277167, acc = 0.840000\n",
      "epoch [  38] L = 57.450387, acc = 0.840000\n",
      "epoch [  39] L = 56.661042, acc = 0.840000\n",
      "epoch [  40] L = 55.908455, acc = 0.840000\n",
      "epoch [  41] L = 55.191754, acc = 0.840000\n",
      "epoch [  42] L = 54.509905, acc = 0.840000\n",
      "epoch [  43] L = 53.861752, acc = 0.840000\n",
      "epoch [  44] L = 53.246040, acc = 0.840000\n",
      "epoch [  45] L = 52.661448, acc = 0.840000\n",
      "epoch [  46] L = 52.106610, acc = 0.840000\n",
      "epoch [  47] L = 51.580140, acc = 0.840000\n",
      "epoch [  48] L = 51.080646, acc = 0.840000\n",
      "epoch [  49] L = 50.606751, acc = 0.835000\n",
      "epoch [  50] L = 50.157100, acc = 0.835000\n",
      "epoch [  51] L = 49.730372, acc = 0.835000\n",
      "epoch [  52] L = 49.325289, acc = 0.835000\n",
      "epoch [  53] L = 48.940621, acc = 0.835000\n",
      "epoch [  54] L = 48.575187, acc = 0.835000\n",
      "epoch [  55] L = 48.227865, acc = 0.835000\n",
      "epoch [  56] L = 47.897584, acc = 0.835000\n",
      "epoch [  57] L = 47.583332, acc = 0.835000\n",
      "epoch [  58] L = 47.284152, acc = 0.835000\n",
      "epoch [  59] L = 46.999144, acc = 0.835000\n",
      "epoch [  60] L = 46.727458, acc = 0.835000\n",
      "epoch [  61] L = 46.468297, acc = 0.835000\n",
      "epoch [  62] L = 46.220916, acc = 0.835000\n",
      "epoch [  63] L = 45.984614, acc = 0.835000\n",
      "epoch [  64] L = 45.758737, acc = 0.835000\n",
      "epoch [  65] L = 45.542672, acc = 0.835000\n",
      "epoch [  66] L = 45.335849, acc = 0.835000\n",
      "epoch [  67] L = 45.137733, acc = 0.835000\n",
      "epoch [  68] L = 44.947825, acc = 0.840000\n",
      "epoch [  69] L = 44.765662, acc = 0.840000\n",
      "epoch [  70] L = 44.590809, acc = 0.840000\n",
      "epoch [  71] L = 44.422860, acc = 0.835000\n",
      "epoch [  72] L = 44.261438, acc = 0.835000\n",
      "epoch [  73] L = 44.106191, acc = 0.835000\n",
      "epoch [  74] L = 43.956790, acc = 0.835000\n",
      "epoch [  75] L = 43.812926, acc = 0.835000\n",
      "epoch [  76] L = 43.674313, acc = 0.835000\n",
      "epoch [  77] L = 43.540682, acc = 0.835000\n",
      "epoch [  78] L = 43.411783, acc = 0.835000\n",
      "epoch [  79] L = 43.287381, acc = 0.835000\n",
      "epoch [  80] L = 43.167257, acc = 0.835000\n",
      "epoch [  81] L = 43.051204, acc = 0.835000\n",
      "epoch [  82] L = 42.939030, acc = 0.835000\n",
      "epoch [  83] L = 42.830555, acc = 0.835000\n",
      "epoch [  84] L = 42.725609, acc = 0.835000\n",
      "epoch [  85] L = 42.624032, acc = 0.830000\n",
      "epoch [  86] L = 42.525675, acc = 0.830000\n",
      "epoch [  87] L = 42.430398, acc = 0.830000\n",
      "epoch [  88] L = 42.338068, acc = 0.830000\n",
      "epoch [  89] L = 42.248560, acc = 0.830000\n",
      "epoch [  90] L = 42.161756, acc = 0.830000\n",
      "epoch [  91] L = 42.077547, acc = 0.830000\n",
      "epoch [  92] L = 41.995826, acc = 0.830000\n",
      "epoch [  93] L = 41.916496, acc = 0.830000\n",
      "epoch [  94] L = 41.839462, acc = 0.830000\n",
      "epoch [  95] L = 41.764636, acc = 0.835000\n",
      "epoch [  96] L = 41.691933, acc = 0.835000\n",
      "epoch [  97] L = 41.621275, acc = 0.835000\n",
      "epoch [  98] L = 41.552586, acc = 0.835000\n",
      "epoch [  99] L = 41.485794, acc = 0.835000\n",
      "epoch [ 100] L = 41.420830, acc = 0.835000\n",
      "epoch [ 101] L = 41.357630, acc = 0.835000\n",
      "epoch [ 102] L = 41.296133, acc = 0.835000\n",
      "epoch [ 103] L = 41.236278, acc = 0.835000\n",
      "epoch [ 104] L = 41.178010, acc = 0.835000\n",
      "epoch [ 105] L = 41.121276, acc = 0.835000\n",
      "epoch [ 106] L = 41.066025, acc = 0.835000\n",
      "epoch [ 107] L = 41.012206, acc = 0.835000\n",
      "epoch [ 108] L = 40.959775, acc = 0.835000\n",
      "epoch [ 109] L = 40.908685, acc = 0.835000\n",
      "epoch [ 110] L = 40.858894, acc = 0.835000\n",
      "epoch [ 111] L = 40.810361, acc = 0.835000\n",
      "epoch [ 112] L = 40.763046, acc = 0.835000\n",
      "epoch [ 113] L = 40.716912, acc = 0.835000\n",
      "epoch [ 114] L = 40.671923, acc = 0.835000\n",
      "epoch [ 115] L = 40.628043, acc = 0.835000\n",
      "epoch [ 116] L = 40.585238, acc = 0.835000\n",
      "epoch [ 117] L = 40.543478, acc = 0.835000\n",
      "epoch [ 118] L = 40.502730, acc = 0.835000\n",
      "epoch [ 119] L = 40.462965, acc = 0.835000\n",
      "epoch [ 120] L = 40.424155, acc = 0.835000\n",
      "epoch [ 121] L = 40.386270, acc = 0.835000\n",
      "epoch [ 122] L = 40.349285, acc = 0.835000\n",
      "epoch [ 123] L = 40.313174, acc = 0.840000\n",
      "epoch [ 124] L = 40.277912, acc = 0.840000\n",
      "epoch [ 125] L = 40.243474, acc = 0.840000\n",
      "epoch [ 126] L = 40.209839, acc = 0.840000\n",
      "epoch [ 127] L = 40.176983, acc = 0.840000\n",
      "epoch [ 128] L = 40.144884, acc = 0.840000\n",
      "epoch [ 129] L = 40.113523, acc = 0.840000\n",
      "epoch [ 130] L = 40.082878, acc = 0.840000\n",
      "epoch [ 131] L = 40.052929, acc = 0.840000\n",
      "epoch [ 132] L = 40.023659, acc = 0.845000\n",
      "epoch [ 133] L = 39.995049, acc = 0.845000\n",
      "epoch [ 134] L = 39.967081, acc = 0.845000\n",
      "epoch [ 135] L = 39.939737, acc = 0.845000\n",
      "epoch [ 136] L = 39.913002, acc = 0.850000\n",
      "epoch [ 137] L = 39.886858, acc = 0.850000\n",
      "epoch [ 138] L = 39.861292, acc = 0.850000\n",
      "epoch [ 139] L = 39.836286, acc = 0.850000\n",
      "epoch [ 140] L = 39.811827, acc = 0.850000\n",
      "epoch [ 141] L = 39.787901, acc = 0.850000\n",
      "epoch [ 142] L = 39.764493, acc = 0.850000\n",
      "epoch [ 143] L = 39.741591, acc = 0.850000\n",
      "epoch [ 144] L = 39.719181, acc = 0.850000\n",
      "epoch [ 145] L = 39.697250, acc = 0.850000\n",
      "epoch [ 146] L = 39.675787, acc = 0.850000\n",
      "epoch [ 147] L = 39.654780, acc = 0.850000\n",
      "epoch [ 148] L = 39.634217, acc = 0.850000\n",
      "epoch [ 149] L = 39.614086, acc = 0.850000\n",
      "epoch [ 150] L = 39.594378, acc = 0.850000\n",
      "epoch [ 151] L = 39.575081, acc = 0.850000\n",
      "epoch [ 152] L = 39.556186, acc = 0.850000\n",
      "epoch [ 153] L = 39.537681, acc = 0.855000\n",
      "epoch [ 154] L = 39.519559, acc = 0.855000\n",
      "epoch [ 155] L = 39.501809, acc = 0.855000\n",
      "epoch [ 156] L = 39.484421, acc = 0.855000\n",
      "epoch [ 157] L = 39.467388, acc = 0.855000\n",
      "epoch [ 158] L = 39.450701, acc = 0.855000\n",
      "epoch [ 159] L = 39.434351, acc = 0.855000\n",
      "epoch [ 160] L = 39.418330, acc = 0.855000\n",
      "epoch [ 161] L = 39.402630, acc = 0.855000\n",
      "epoch [ 162] L = 39.387244, acc = 0.855000\n",
      "epoch [ 163] L = 39.372164, acc = 0.855000\n",
      "epoch [ 164] L = 39.357382, acc = 0.855000\n",
      "epoch [ 165] L = 39.342892, acc = 0.855000\n",
      "epoch [ 166] L = 39.328686, acc = 0.855000\n",
      "epoch [ 167] L = 39.314759, acc = 0.855000\n",
      "epoch [ 168] L = 39.301103, acc = 0.855000\n",
      "epoch [ 169] L = 39.287712, acc = 0.855000\n",
      "epoch [ 170] L = 39.274579, acc = 0.855000\n",
      "epoch [ 171] L = 39.261700, acc = 0.855000\n",
      "epoch [ 172] L = 39.249068, acc = 0.855000\n",
      "epoch [ 173] L = 39.236677, acc = 0.855000\n",
      "epoch [ 174] L = 39.224521, acc = 0.855000\n",
      "epoch [ 175] L = 39.212596, acc = 0.855000\n",
      "epoch [ 176] L = 39.200896, acc = 0.855000\n",
      "epoch [ 177] L = 39.189416, acc = 0.855000\n",
      "epoch [ 178] L = 39.178151, acc = 0.855000\n",
      "epoch [ 179] L = 39.167096, acc = 0.855000\n",
      "epoch [ 180] L = 39.156246, acc = 0.855000\n",
      "epoch [ 181] L = 39.145597, acc = 0.855000\n",
      "epoch [ 182] L = 39.135144, acc = 0.855000\n",
      "epoch [ 183] L = 39.124882, acc = 0.855000\n",
      "epoch [ 184] L = 39.114808, acc = 0.855000\n",
      "epoch [ 185] L = 39.104918, acc = 0.855000\n",
      "epoch [ 186] L = 39.095207, acc = 0.855000\n",
      "epoch [ 187] L = 39.085671, acc = 0.855000\n",
      "epoch [ 188] L = 39.076306, acc = 0.855000\n",
      "epoch [ 189] L = 39.067109, acc = 0.855000\n",
      "epoch [ 190] L = 39.058077, acc = 0.855000\n",
      "epoch [ 191] L = 39.049204, acc = 0.855000\n",
      "epoch [ 192] L = 39.040489, acc = 0.855000\n",
      "epoch [ 193] L = 39.031927, acc = 0.855000\n",
      "epoch [ 194] L = 39.023515, acc = 0.855000\n",
      "epoch [ 195] L = 39.015250, acc = 0.855000\n",
      "epoch [ 196] L = 39.007130, acc = 0.855000\n",
      "epoch [ 197] L = 38.999149, acc = 0.855000\n",
      "epoch [ 198] L = 38.991307, acc = 0.855000\n",
      "epoch [ 199] L = 38.983599, acc = 0.855000\n",
      "epoch [ 200] L = 38.976024, acc = 0.855000\n",
      "epoch [ 201] L = 38.968577, acc = 0.855000\n",
      "epoch [ 202] L = 38.961257, acc = 0.855000\n",
      "epoch [ 203] L = 38.954061, acc = 0.855000\n",
      "epoch [ 204] L = 38.946986, acc = 0.855000\n",
      "epoch [ 205] L = 38.940030, acc = 0.855000\n",
      "epoch [ 206] L = 38.933189, acc = 0.855000\n",
      "epoch [ 207] L = 38.926463, acc = 0.855000\n",
      "epoch [ 208] L = 38.919847, acc = 0.855000\n",
      "epoch [ 209] L = 38.913341, acc = 0.855000\n",
      "epoch [ 210] L = 38.906942, acc = 0.855000\n",
      "epoch [ 211] L = 38.900648, acc = 0.855000\n",
      "epoch [ 212] L = 38.894455, acc = 0.855000\n",
      "epoch [ 213] L = 38.888364, acc = 0.855000\n",
      "epoch [ 214] L = 38.882370, acc = 0.855000\n",
      "epoch [ 215] L = 38.876473, acc = 0.855000\n",
      "epoch [ 216] L = 38.870671, acc = 0.855000\n",
      "epoch [ 217] L = 38.864960, acc = 0.855000\n",
      "epoch [ 218] L = 38.859341, acc = 0.855000\n",
      "epoch [ 219] L = 38.853810, acc = 0.855000\n",
      "epoch [ 220] L = 38.848366, acc = 0.855000\n",
      "epoch [ 221] L = 38.843008, acc = 0.855000\n",
      "epoch [ 222] L = 38.837733, acc = 0.855000\n",
      "epoch [ 223] L = 38.832539, acc = 0.855000\n",
      "epoch [ 224] L = 38.827427, acc = 0.855000\n",
      "epoch [ 225] L = 38.822392, acc = 0.855000\n",
      "epoch [ 226] L = 38.817435, acc = 0.855000\n",
      "epoch [ 227] L = 38.812554, acc = 0.855000\n",
      "epoch [ 228] L = 38.807747, acc = 0.855000\n",
      "epoch [ 229] L = 38.803012, acc = 0.855000\n",
      "epoch [ 230] L = 38.798348, acc = 0.855000\n",
      "epoch [ 231] L = 38.793755, acc = 0.855000\n",
      "epoch [ 232] L = 38.789229, acc = 0.855000\n",
      "epoch [ 233] L = 38.784771, acc = 0.855000\n",
      "epoch [ 234] L = 38.780379, acc = 0.855000\n",
      "epoch [ 235] L = 38.776051, acc = 0.855000\n",
      "epoch [ 236] L = 38.771787, acc = 0.855000\n",
      "epoch [ 237] L = 38.767585, acc = 0.855000\n",
      "epoch [ 238] L = 38.763443, acc = 0.855000\n",
      "epoch [ 239] L = 38.759361, acc = 0.855000\n",
      "epoch [ 240] L = 38.755338, acc = 0.855000\n",
      "epoch [ 241] L = 38.751373, acc = 0.855000\n",
      "epoch [ 242] L = 38.747463, acc = 0.855000\n",
      "epoch [ 243] L = 38.743609, acc = 0.855000\n",
      "epoch [ 244] L = 38.739809, acc = 0.855000\n",
      "epoch [ 245] L = 38.736062, acc = 0.855000\n",
      "epoch [ 246] L = 38.732368, acc = 0.855000\n",
      "epoch [ 247] L = 38.728725, acc = 0.855000\n",
      "epoch [ 248] L = 38.725131, acc = 0.855000\n",
      "epoch [ 249] L = 38.721588, acc = 0.855000\n",
      "epoch [ 250] L = 38.718092, acc = 0.855000\n",
      "epoch [ 251] L = 38.714644, acc = 0.855000\n",
      "epoch [ 252] L = 38.711243, acc = 0.855000\n",
      "epoch [ 253] L = 38.707887, acc = 0.855000\n",
      "epoch [ 254] L = 38.704576, acc = 0.855000\n",
      "epoch [ 255] L = 38.701309, acc = 0.855000\n",
      "epoch [ 256] L = 38.698085, acc = 0.855000\n",
      "epoch [ 257] L = 38.694903, acc = 0.855000\n",
      "epoch [ 258] L = 38.691763, acc = 0.855000\n",
      "epoch [ 259] L = 38.688664, acc = 0.855000\n",
      "epoch [ 260] L = 38.685605, acc = 0.855000\n",
      "epoch [ 261] L = 38.682585, acc = 0.855000\n",
      "epoch [ 262] L = 38.679604, acc = 0.855000\n",
      "epoch [ 263] L = 38.676660, acc = 0.855000\n",
      "epoch [ 264] L = 38.673754, acc = 0.855000\n",
      "epoch [ 265] L = 38.670884, acc = 0.855000\n",
      "epoch [ 266] L = 38.668050, acc = 0.855000\n",
      "epoch [ 267] L = 38.665251, acc = 0.855000\n",
      "epoch [ 268] L = 38.662487, acc = 0.855000\n",
      "epoch [ 269] L = 38.659756, acc = 0.855000\n",
      "epoch [ 270] L = 38.657059, acc = 0.855000\n",
      "epoch [ 271] L = 38.654394, acc = 0.855000\n",
      "epoch [ 272] L = 38.651761, acc = 0.855000\n",
      "epoch [ 273] L = 38.649160, acc = 0.855000\n",
      "epoch [ 274] L = 38.646589, acc = 0.855000\n",
      "epoch [ 275] L = 38.644049, acc = 0.855000\n",
      "epoch [ 276] L = 38.641538, acc = 0.855000\n",
      "epoch [ 277] L = 38.639057, acc = 0.855000\n",
      "epoch [ 278] L = 38.636604, acc = 0.855000\n",
      "epoch [ 279] L = 38.634180, acc = 0.855000\n",
      "epoch [ 280] L = 38.631783, acc = 0.855000\n",
      "epoch [ 281] L = 38.629413, acc = 0.855000\n",
      "epoch [ 282] L = 38.627070, acc = 0.855000\n",
      "epoch [ 283] L = 38.624753, acc = 0.855000\n",
      "epoch [ 284] L = 38.622461, acc = 0.855000\n",
      "epoch [ 285] L = 38.620195, acc = 0.855000\n",
      "epoch [ 286] L = 38.617953, acc = 0.855000\n",
      "epoch [ 287] L = 38.615736, acc = 0.855000\n",
      "epoch [ 288] L = 38.613543, acc = 0.855000\n",
      "epoch [ 289] L = 38.611372, acc = 0.855000\n",
      "epoch [ 290] L = 38.609225, acc = 0.855000\n",
      "epoch [ 291] L = 38.607101, acc = 0.855000\n",
      "epoch [ 292] L = 38.604998, acc = 0.855000\n",
      "epoch [ 293] L = 38.602917, acc = 0.855000\n",
      "epoch [ 294] L = 38.600858, acc = 0.855000\n",
      "epoch [ 295] L = 38.598819, acc = 0.855000\n",
      "epoch [ 296] L = 38.596801, acc = 0.855000\n",
      "epoch [ 297] L = 38.594803, acc = 0.855000\n",
      "epoch [ 298] L = 38.592825, acc = 0.855000\n",
      "epoch [ 299] L = 38.590866, acc = 0.855000\n",
      "epoch [ 300] L = 38.588926, acc = 0.855000\n",
      "epoch [ 301] L = 38.587005, acc = 0.855000\n",
      "epoch [ 302] L = 38.585102, acc = 0.855000\n",
      "epoch [ 303] L = 38.583218, acc = 0.855000\n",
      "epoch [ 304] L = 38.581351, acc = 0.855000\n",
      "epoch [ 305] L = 38.579501, acc = 0.855000\n",
      "epoch [ 306] L = 38.577668, acc = 0.855000\n",
      "epoch [ 307] L = 38.575852, acc = 0.855000\n",
      "epoch [ 308] L = 38.574053, acc = 0.855000\n",
      "epoch [ 309] L = 38.572269, acc = 0.855000\n",
      "epoch [ 310] L = 38.570502, acc = 0.855000\n",
      "epoch [ 311] L = 38.568749, acc = 0.855000\n",
      "epoch [ 312] L = 38.567012, acc = 0.855000\n",
      "epoch [ 313] L = 38.565290, acc = 0.855000\n",
      "epoch [ 314] L = 38.563582, acc = 0.850000\n",
      "epoch [ 315] L = 38.561889, acc = 0.850000\n",
      "epoch [ 316] L = 38.560210, acc = 0.850000\n",
      "epoch [ 317] L = 38.558544, acc = 0.850000\n",
      "epoch [ 318] L = 38.556893, acc = 0.850000\n",
      "epoch [ 319] L = 38.555254, acc = 0.850000\n",
      "epoch [ 320] L = 38.553628, acc = 0.850000\n",
      "epoch [ 321] L = 38.552015, acc = 0.850000\n",
      "epoch [ 322] L = 38.550415, acc = 0.850000\n",
      "epoch [ 323] L = 38.548827, acc = 0.850000\n",
      "epoch [ 324] L = 38.547250, acc = 0.845000\n",
      "epoch [ 325] L = 38.545686, acc = 0.845000\n",
      "epoch [ 326] L = 38.544133, acc = 0.845000\n",
      "epoch [ 327] L = 38.542592, acc = 0.845000\n",
      "epoch [ 328] L = 38.541061, acc = 0.845000\n",
      "epoch [ 329] L = 38.539541, acc = 0.845000\n",
      "epoch [ 330] L = 38.538032, acc = 0.845000\n",
      "epoch [ 331] L = 38.536534, acc = 0.845000\n",
      "epoch [ 332] L = 38.535045, acc = 0.845000\n",
      "epoch [ 333] L = 38.533567, acc = 0.845000\n",
      "epoch [ 334] L = 38.532098, acc = 0.845000\n",
      "epoch [ 335] L = 38.530639, acc = 0.845000\n",
      "epoch [ 336] L = 38.529189, acc = 0.845000\n",
      "epoch [ 337] L = 38.527748, acc = 0.845000\n",
      "epoch [ 338] L = 38.526317, acc = 0.845000\n",
      "epoch [ 339] L = 38.524894, acc = 0.845000\n",
      "epoch [ 340] L = 38.523479, acc = 0.845000\n",
      "epoch [ 341] L = 38.522073, acc = 0.845000\n",
      "epoch [ 342] L = 38.520676, acc = 0.845000\n",
      "epoch [ 343] L = 38.519286, acc = 0.845000\n",
      "epoch [ 344] L = 38.517904, acc = 0.845000\n",
      "epoch [ 345] L = 38.516530, acc = 0.845000\n",
      "epoch [ 346] L = 38.515163, acc = 0.845000\n",
      "epoch [ 347] L = 38.513804, acc = 0.845000\n",
      "epoch [ 348] L = 38.512452, acc = 0.845000\n",
      "epoch [ 349] L = 38.511107, acc = 0.845000\n",
      "epoch [ 350] L = 38.509768, acc = 0.845000\n",
      "epoch [ 351] L = 38.508437, acc = 0.845000\n",
      "epoch [ 352] L = 38.507111, acc = 0.845000\n",
      "epoch [ 353] L = 38.505792, acc = 0.845000\n",
      "epoch [ 354] L = 38.504480, acc = 0.845000\n",
      "epoch [ 355] L = 38.503173, acc = 0.845000\n",
      "epoch [ 356] L = 38.501872, acc = 0.845000\n",
      "epoch [ 357] L = 38.500577, acc = 0.845000\n",
      "epoch [ 358] L = 38.499287, acc = 0.845000\n",
      "epoch [ 359] L = 38.498003, acc = 0.845000\n",
      "epoch [ 360] L = 38.496724, acc = 0.845000\n",
      "epoch [ 361] L = 38.495450, acc = 0.845000\n",
      "epoch [ 362] L = 38.494182, acc = 0.850000\n",
      "epoch [ 363] L = 38.492918, acc = 0.850000\n",
      "epoch [ 364] L = 38.491658, acc = 0.850000\n",
      "epoch [ 365] L = 38.490404, acc = 0.850000\n",
      "epoch [ 366] L = 38.489154, acc = 0.850000\n",
      "epoch [ 367] L = 38.487908, acc = 0.850000\n",
      "epoch [ 368] L = 38.486666, acc = 0.850000\n",
      "epoch [ 369] L = 38.485428, acc = 0.850000\n",
      "epoch [ 370] L = 38.484194, acc = 0.850000\n",
      "epoch [ 371] L = 38.482964, acc = 0.850000\n",
      "epoch [ 372] L = 38.481738, acc = 0.850000\n",
      "epoch [ 373] L = 38.480515, acc = 0.850000\n",
      "epoch [ 374] L = 38.479295, acc = 0.850000\n",
      "epoch [ 375] L = 38.478079, acc = 0.850000\n",
      "epoch [ 376] L = 38.476866, acc = 0.850000\n",
      "epoch [ 377] L = 38.475656, acc = 0.850000\n",
      "epoch [ 378] L = 38.474449, acc = 0.850000\n",
      "epoch [ 379] L = 38.473245, acc = 0.850000\n",
      "epoch [ 380] L = 38.472043, acc = 0.850000\n",
      "epoch [ 381] L = 38.470844, acc = 0.850000\n",
      "epoch [ 382] L = 38.469648, acc = 0.850000\n",
      "epoch [ 383] L = 38.468454, acc = 0.850000\n",
      "epoch [ 384] L = 38.467262, acc = 0.850000\n",
      "epoch [ 385] L = 38.466072, acc = 0.850000\n",
      "epoch [ 386] L = 38.464884, acc = 0.850000\n",
      "epoch [ 387] L = 38.463698, acc = 0.850000\n",
      "epoch [ 388] L = 38.462514, acc = 0.850000\n",
      "epoch [ 389] L = 38.461332, acc = 0.850000\n",
      "epoch [ 390] L = 38.460151, acc = 0.850000\n",
      "epoch [ 391] L = 38.458972, acc = 0.850000\n",
      "epoch [ 392] L = 38.457794, acc = 0.850000\n",
      "epoch [ 393] L = 38.456617, acc = 0.850000\n",
      "epoch [ 394] L = 38.455442, acc = 0.850000\n",
      "epoch [ 395] L = 38.454267, acc = 0.850000\n",
      "epoch [ 396] L = 38.453094, acc = 0.850000\n",
      "epoch [ 397] L = 38.451922, acc = 0.850000\n",
      "epoch [ 398] L = 38.450750, acc = 0.850000\n",
      "epoch [ 399] L = 38.449579, acc = 0.850000\n",
      "epoch [ 400] L = 38.448409, acc = 0.850000\n",
      "epoch [ 401] L = 38.447239, acc = 0.850000\n",
      "epoch [ 402] L = 38.446069, acc = 0.850000\n",
      "epoch [ 403] L = 38.444900, acc = 0.850000\n",
      "epoch [ 404] L = 38.443731, acc = 0.850000\n",
      "epoch [ 405] L = 38.442563, acc = 0.850000\n",
      "epoch [ 406] L = 38.441394, acc = 0.850000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch [ 407] L = 38.440225, acc = 0.850000\n",
      "epoch [ 408] L = 38.439056, acc = 0.850000\n",
      "epoch [ 409] L = 38.437887, acc = 0.850000\n",
      "epoch [ 410] L = 38.436718, acc = 0.850000\n",
      "epoch [ 411] L = 38.435548, acc = 0.850000\n",
      "epoch [ 412] L = 38.434378, acc = 0.850000\n",
      "epoch [ 413] L = 38.433207, acc = 0.850000\n",
      "epoch [ 414] L = 38.432035, acc = 0.850000\n",
      "epoch [ 415] L = 38.430863, acc = 0.850000\n",
      "epoch [ 416] L = 38.429690, acc = 0.850000\n",
      "epoch [ 417] L = 38.428516, acc = 0.850000\n",
      "epoch [ 418] L = 38.427341, acc = 0.850000\n",
      "epoch [ 419] L = 38.426165, acc = 0.850000\n",
      "epoch [ 420] L = 38.424987, acc = 0.850000\n",
      "epoch [ 421] L = 38.423809, acc = 0.850000\n",
      "epoch [ 422] L = 38.422629, acc = 0.850000\n",
      "epoch [ 423] L = 38.421448, acc = 0.850000\n",
      "epoch [ 424] L = 38.420265, acc = 0.850000\n",
      "epoch [ 425] L = 38.419081, acc = 0.850000\n",
      "epoch [ 426] L = 38.417895, acc = 0.850000\n",
      "epoch [ 427] L = 38.416707, acc = 0.850000\n",
      "epoch [ 428] L = 38.415517, acc = 0.850000\n",
      "epoch [ 429] L = 38.414326, acc = 0.850000\n",
      "epoch [ 430] L = 38.413132, acc = 0.850000\n",
      "epoch [ 431] L = 38.411937, acc = 0.850000\n",
      "epoch [ 432] L = 38.410739, acc = 0.850000\n",
      "epoch [ 433] L = 38.409540, acc = 0.850000\n",
      "epoch [ 434] L = 38.408338, acc = 0.850000\n",
      "epoch [ 435] L = 38.407133, acc = 0.850000\n",
      "epoch [ 436] L = 38.405926, acc = 0.850000\n",
      "epoch [ 437] L = 38.404717, acc = 0.850000\n",
      "epoch [ 438] L = 38.403505, acc = 0.850000\n",
      "epoch [ 439] L = 38.402291, acc = 0.850000\n",
      "epoch [ 440] L = 38.401073, acc = 0.850000\n",
      "epoch [ 441] L = 38.399853, acc = 0.850000\n",
      "epoch [ 442] L = 38.398630, acc = 0.850000\n",
      "epoch [ 443] L = 38.397404, acc = 0.850000\n",
      "epoch [ 444] L = 38.396175, acc = 0.850000\n",
      "epoch [ 445] L = 38.394943, acc = 0.850000\n",
      "epoch [ 446] L = 38.393708, acc = 0.850000\n",
      "epoch [ 447] L = 38.392470, acc = 0.850000\n",
      "epoch [ 448] L = 38.391228, acc = 0.850000\n",
      "epoch [ 449] L = 38.389982, acc = 0.850000\n",
      "epoch [ 450] L = 38.388734, acc = 0.850000\n",
      "epoch [ 451] L = 38.387482, acc = 0.850000\n",
      "epoch [ 452] L = 38.386226, acc = 0.850000\n",
      "epoch [ 453] L = 38.384966, acc = 0.850000\n",
      "epoch [ 454] L = 38.383703, acc = 0.850000\n",
      "epoch [ 455] L = 38.382436, acc = 0.850000\n",
      "epoch [ 456] L = 38.381165, acc = 0.850000\n",
      "epoch [ 457] L = 38.379890, acc = 0.850000\n",
      "epoch [ 458] L = 38.378611, acc = 0.850000\n",
      "epoch [ 459] L = 38.377328, acc = 0.850000\n",
      "epoch [ 460] L = 38.376040, acc = 0.850000\n",
      "epoch [ 461] L = 38.374749, acc = 0.850000\n",
      "epoch [ 462] L = 38.373453, acc = 0.850000\n",
      "epoch [ 463] L = 38.372153, acc = 0.850000\n",
      "epoch [ 464] L = 38.370848, acc = 0.850000\n",
      "epoch [ 465] L = 38.369539, acc = 0.850000\n",
      "epoch [ 466] L = 38.368225, acc = 0.850000\n",
      "epoch [ 467] L = 38.366906, acc = 0.850000\n",
      "epoch [ 468] L = 38.365583, acc = 0.850000\n",
      "epoch [ 469] L = 38.364255, acc = 0.850000\n",
      "epoch [ 470] L = 38.362922, acc = 0.850000\n",
      "epoch [ 471] L = 38.361584, acc = 0.850000\n",
      "epoch [ 472] L = 38.360240, acc = 0.850000\n",
      "epoch [ 473] L = 38.358892, acc = 0.850000\n",
      "epoch [ 474] L = 38.357539, acc = 0.850000\n",
      "epoch [ 475] L = 38.356180, acc = 0.850000\n",
      "epoch [ 476] L = 38.354817, acc = 0.850000\n",
      "epoch [ 477] L = 38.353447, acc = 0.850000\n",
      "epoch [ 478] L = 38.352073, acc = 0.850000\n",
      "epoch [ 479] L = 38.350692, acc = 0.850000\n",
      "epoch [ 480] L = 38.349306, acc = 0.850000\n",
      "epoch [ 481] L = 38.347915, acc = 0.850000\n",
      "epoch [ 482] L = 38.346518, acc = 0.850000\n",
      "epoch [ 483] L = 38.345115, acc = 0.850000\n",
      "epoch [ 484] L = 38.343706, acc = 0.850000\n",
      "epoch [ 485] L = 38.342291, acc = 0.850000\n",
      "epoch [ 486] L = 38.340870, acc = 0.850000\n",
      "epoch [ 487] L = 38.339443, acc = 0.850000\n",
      "epoch [ 488] L = 38.338010, acc = 0.850000\n",
      "epoch [ 489] L = 38.336570, acc = 0.850000\n",
      "epoch [ 490] L = 38.335125, acc = 0.850000\n",
      "epoch [ 491] L = 38.333673, acc = 0.850000\n",
      "epoch [ 492] L = 38.332214, acc = 0.850000\n",
      "epoch [ 493] L = 38.330749, acc = 0.850000\n",
      "epoch [ 494] L = 38.329277, acc = 0.850000\n",
      "epoch [ 495] L = 38.327799, acc = 0.850000\n",
      "epoch [ 496] L = 38.326314, acc = 0.850000\n",
      "epoch [ 497] L = 38.324822, acc = 0.850000\n",
      "epoch [ 498] L = 38.323323, acc = 0.850000\n",
      "epoch [ 499] L = 38.321818, acc = 0.850000\n",
      "epoch [ 500] L = 38.320305, acc = 0.850000\n",
      "epoch [ 501] L = 38.318785, acc = 0.850000\n",
      "epoch [ 502] L = 38.317258, acc = 0.850000\n",
      "epoch [ 503] L = 38.315724, acc = 0.850000\n",
      "epoch [ 504] L = 38.314182, acc = 0.850000\n",
      "epoch [ 505] L = 38.312633, acc = 0.850000\n",
      "epoch [ 506] L = 38.311077, acc = 0.850000\n",
      "epoch [ 507] L = 38.309513, acc = 0.850000\n",
      "epoch [ 508] L = 38.307941, acc = 0.850000\n",
      "epoch [ 509] L = 38.306362, acc = 0.850000\n",
      "epoch [ 510] L = 38.304775, acc = 0.850000\n",
      "epoch [ 511] L = 38.303180, acc = 0.850000\n",
      "epoch [ 512] L = 38.301577, acc = 0.850000\n",
      "epoch [ 513] L = 38.299966, acc = 0.850000\n",
      "epoch [ 514] L = 38.298347, acc = 0.850000\n",
      "epoch [ 515] L = 38.296720, acc = 0.850000\n",
      "epoch [ 516] L = 38.295085, acc = 0.850000\n",
      "epoch [ 517] L = 38.293441, acc = 0.850000\n",
      "epoch [ 518] L = 38.291789, acc = 0.850000\n",
      "epoch [ 519] L = 38.290129, acc = 0.850000\n",
      "epoch [ 520] L = 38.288460, acc = 0.850000\n",
      "epoch [ 521] L = 38.286782, acc = 0.850000\n",
      "epoch [ 522] L = 38.285096, acc = 0.850000\n",
      "epoch [ 523] L = 38.283401, acc = 0.850000\n",
      "epoch [ 524] L = 38.281697, acc = 0.850000\n",
      "epoch [ 525] L = 38.279984, acc = 0.850000\n",
      "epoch [ 526] L = 38.278262, acc = 0.850000\n",
      "epoch [ 527] L = 38.276531, acc = 0.850000\n",
      "epoch [ 528] L = 38.274791, acc = 0.850000\n",
      "epoch [ 529] L = 38.273041, acc = 0.850000\n",
      "epoch [ 530] L = 38.271282, acc = 0.850000\n",
      "epoch [ 531] L = 38.269514, acc = 0.850000\n",
      "epoch [ 532] L = 38.267736, acc = 0.850000\n",
      "epoch [ 533] L = 38.265949, acc = 0.850000\n",
      "epoch [ 534] L = 38.264152, acc = 0.850000\n",
      "epoch [ 535] L = 38.262345, acc = 0.850000\n",
      "epoch [ 536] L = 38.260528, acc = 0.850000\n",
      "epoch [ 537] L = 38.258702, acc = 0.850000\n",
      "epoch [ 538] L = 38.256865, acc = 0.850000\n",
      "epoch [ 539] L = 38.255018, acc = 0.850000\n",
      "epoch [ 540] L = 38.253161, acc = 0.850000\n",
      "epoch [ 541] L = 38.251294, acc = 0.850000\n",
      "epoch [ 542] L = 38.249416, acc = 0.850000\n",
      "epoch [ 543] L = 38.247528, acc = 0.850000\n",
      "epoch [ 544] L = 38.245630, acc = 0.850000\n",
      "epoch [ 545] L = 38.243720, acc = 0.850000\n",
      "epoch [ 546] L = 38.241800, acc = 0.850000\n",
      "epoch [ 547] L = 38.239869, acc = 0.850000\n",
      "epoch [ 548] L = 38.237928, acc = 0.850000\n",
      "epoch [ 549] L = 38.235975, acc = 0.850000\n",
      "epoch [ 550] L = 38.234011, acc = 0.850000\n",
      "epoch [ 551] L = 38.232036, acc = 0.850000\n",
      "epoch [ 552] L = 38.230049, acc = 0.850000\n",
      "epoch [ 553] L = 38.228051, acc = 0.850000\n",
      "epoch [ 554] L = 38.226042, acc = 0.850000\n",
      "epoch [ 555] L = 38.224021, acc = 0.850000\n",
      "epoch [ 556] L = 38.221988, acc = 0.850000\n",
      "epoch [ 557] L = 38.219944, acc = 0.850000\n",
      "epoch [ 558] L = 38.217888, acc = 0.850000\n",
      "epoch [ 559] L = 38.215819, acc = 0.850000\n",
      "epoch [ 560] L = 38.213739, acc = 0.850000\n",
      "epoch [ 561] L = 38.211646, acc = 0.850000\n",
      "epoch [ 562] L = 38.209541, acc = 0.850000\n",
      "epoch [ 563] L = 38.207424, acc = 0.850000\n",
      "epoch [ 564] L = 38.205294, acc = 0.850000\n",
      "epoch [ 565] L = 38.203152, acc = 0.850000\n",
      "epoch [ 566] L = 38.200997, acc = 0.850000\n",
      "epoch [ 567] L = 38.198829, acc = 0.850000\n",
      "epoch [ 568] L = 38.196648, acc = 0.850000\n",
      "epoch [ 569] L = 38.194455, acc = 0.855000\n",
      "epoch [ 570] L = 38.192248, acc = 0.855000\n",
      "epoch [ 571] L = 38.190027, acc = 0.855000\n",
      "epoch [ 572] L = 38.187794, acc = 0.855000\n",
      "epoch [ 573] L = 38.185547, acc = 0.855000\n",
      "epoch [ 574] L = 38.183286, acc = 0.855000\n",
      "epoch [ 575] L = 38.181012, acc = 0.855000\n",
      "epoch [ 576] L = 38.178724, acc = 0.855000\n",
      "epoch [ 577] L = 38.176422, acc = 0.855000\n",
      "epoch [ 578] L = 38.174106, acc = 0.855000\n",
      "epoch [ 579] L = 38.171775, acc = 0.855000\n",
      "epoch [ 580] L = 38.169431, acc = 0.860000\n",
      "epoch [ 581] L = 38.167072, acc = 0.860000\n",
      "epoch [ 582] L = 38.164698, acc = 0.860000\n",
      "epoch [ 583] L = 38.162310, acc = 0.860000\n",
      "epoch [ 584] L = 38.159907, acc = 0.860000\n",
      "epoch [ 585] L = 38.157489, acc = 0.860000\n",
      "epoch [ 586] L = 38.155057, acc = 0.860000\n",
      "epoch [ 587] L = 38.152609, acc = 0.860000\n",
      "epoch [ 588] L = 38.150146, acc = 0.860000\n",
      "epoch [ 589] L = 38.147667, acc = 0.860000\n",
      "epoch [ 590] L = 38.145173, acc = 0.860000\n",
      "epoch [ 591] L = 38.142663, acc = 0.860000\n",
      "epoch [ 592] L = 38.140137, acc = 0.860000\n",
      "epoch [ 593] L = 38.137596, acc = 0.860000\n",
      "epoch [ 594] L = 38.135038, acc = 0.860000\n",
      "epoch [ 595] L = 38.132465, acc = 0.860000\n",
      "epoch [ 596] L = 38.129875, acc = 0.860000\n",
      "epoch [ 597] L = 38.127268, acc = 0.860000\n",
      "epoch [ 598] L = 38.124645, acc = 0.860000\n",
      "epoch [ 599] L = 38.122005, acc = 0.860000\n",
      "epoch [ 600] L = 38.119348, acc = 0.860000\n",
      "epoch [ 601] L = 38.116675, acc = 0.860000\n",
      "epoch [ 602] L = 38.113984, acc = 0.860000\n",
      "epoch [ 603] L = 38.111275, acc = 0.860000\n",
      "epoch [ 604] L = 38.108550, acc = 0.860000\n",
      "epoch [ 605] L = 38.105806, acc = 0.860000\n",
      "epoch [ 606] L = 38.103045, acc = 0.860000\n",
      "epoch [ 607] L = 38.100266, acc = 0.860000\n",
      "epoch [ 608] L = 38.097469, acc = 0.860000\n",
      "epoch [ 609] L = 38.094653, acc = 0.860000\n",
      "epoch [ 610] L = 38.091820, acc = 0.860000\n",
      "epoch [ 611] L = 38.088968, acc = 0.860000\n",
      "epoch [ 612] L = 38.086097, acc = 0.860000\n",
      "epoch [ 613] L = 38.083207, acc = 0.860000\n",
      "epoch [ 614] L = 38.080298, acc = 0.860000\n",
      "epoch [ 615] L = 38.077370, acc = 0.860000\n",
      "epoch [ 616] L = 38.074423, acc = 0.860000\n",
      "epoch [ 617] L = 38.071456, acc = 0.860000\n",
      "epoch [ 618] L = 38.068469, acc = 0.860000\n",
      "epoch [ 619] L = 38.065463, acc = 0.860000\n",
      "epoch [ 620] L = 38.062437, acc = 0.860000\n",
      "epoch [ 621] L = 38.059390, acc = 0.860000\n",
      "epoch [ 622] L = 38.056323, acc = 0.860000\n",
      "epoch [ 623] L = 38.053236, acc = 0.860000\n",
      "epoch [ 624] L = 38.050128, acc = 0.860000\n",
      "epoch [ 625] L = 38.046998, acc = 0.860000\n",
      "epoch [ 626] L = 38.043848, acc = 0.860000\n",
      "epoch [ 627] L = 38.040677, acc = 0.860000\n",
      "epoch [ 628] L = 38.037484, acc = 0.860000\n",
      "epoch [ 629] L = 38.034270, acc = 0.860000\n",
      "epoch [ 630] L = 38.031034, acc = 0.860000\n",
      "epoch [ 631] L = 38.027775, acc = 0.860000\n",
      "epoch [ 632] L = 38.024495, acc = 0.860000\n",
      "epoch [ 633] L = 38.021192, acc = 0.860000\n",
      "epoch [ 634] L = 38.017867, acc = 0.860000\n",
      "epoch [ 635] L = 38.014519, acc = 0.860000\n",
      "epoch [ 636] L = 38.011148, acc = 0.860000\n",
      "epoch [ 637] L = 38.007753, acc = 0.860000\n",
      "epoch [ 638] L = 38.004336, acc = 0.860000\n",
      "epoch [ 639] L = 38.000894, acc = 0.860000\n",
      "epoch [ 640] L = 37.997430, acc = 0.860000\n",
      "epoch [ 641] L = 37.993941, acc = 0.860000\n",
      "epoch [ 642] L = 37.990427, acc = 0.860000\n",
      "epoch [ 643] L = 37.986890, acc = 0.860000\n",
      "epoch [ 644] L = 37.983328, acc = 0.860000\n",
      "epoch [ 645] L = 37.979741, acc = 0.860000\n",
      "epoch [ 646] L = 37.976129, acc = 0.860000\n",
      "epoch [ 647] L = 37.972492, acc = 0.860000\n",
      "epoch [ 648] L = 37.968829, acc = 0.860000\n",
      "epoch [ 649] L = 37.965140, acc = 0.860000\n",
      "epoch [ 650] L = 37.961426, acc = 0.860000\n",
      "epoch [ 651] L = 37.957686, acc = 0.860000\n",
      "epoch [ 652] L = 37.953919, acc = 0.860000\n",
      "epoch [ 653] L = 37.950125, acc = 0.860000\n",
      "epoch [ 654] L = 37.946305, acc = 0.860000\n",
      "epoch [ 655] L = 37.942458, acc = 0.860000\n",
      "epoch [ 656] L = 37.938583, acc = 0.860000\n",
      "epoch [ 657] L = 37.934681, acc = 0.860000\n",
      "epoch [ 658] L = 37.930751, acc = 0.860000\n",
      "epoch [ 659] L = 37.926793, acc = 0.860000\n",
      "epoch [ 660] L = 37.922806, acc = 0.860000\n",
      "epoch [ 661] L = 37.918792, acc = 0.860000\n",
      "epoch [ 662] L = 37.914748, acc = 0.860000\n",
      "epoch [ 663] L = 37.910676, acc = 0.860000\n",
      "epoch [ 664] L = 37.906574, acc = 0.860000\n",
      "epoch [ 665] L = 37.902442, acc = 0.860000\n",
      "epoch [ 666] L = 37.898281, acc = 0.860000\n",
      "epoch [ 667] L = 37.894090, acc = 0.860000\n",
      "epoch [ 668] L = 37.889869, acc = 0.860000\n",
      "epoch [ 669] L = 37.885617, acc = 0.860000\n",
      "epoch [ 670] L = 37.881334, acc = 0.860000\n",
      "epoch [ 671] L = 37.877020, acc = 0.860000\n",
      "epoch [ 672] L = 37.872675, acc = 0.860000\n",
      "epoch [ 673] L = 37.868298, acc = 0.860000\n",
      "epoch [ 674] L = 37.863890, acc = 0.860000\n",
      "epoch [ 675] L = 37.859449, acc = 0.860000\n",
      "epoch [ 676] L = 37.854976, acc = 0.860000\n",
      "epoch [ 677] L = 37.850470, acc = 0.860000\n",
      "epoch [ 678] L = 37.845931, acc = 0.860000\n",
      "epoch [ 679] L = 37.841358, acc = 0.860000\n",
      "epoch [ 680] L = 37.836753, acc = 0.860000\n",
      "epoch [ 681] L = 37.832113, acc = 0.860000\n",
      "epoch [ 682] L = 37.827439, acc = 0.860000\n",
      "epoch [ 683] L = 37.822731, acc = 0.860000\n",
      "epoch [ 684] L = 37.817988, acc = 0.860000\n",
      "epoch [ 685] L = 37.813210, acc = 0.860000\n",
      "epoch [ 686] L = 37.808397, acc = 0.860000\n",
      "epoch [ 687] L = 37.803548, acc = 0.860000\n",
      "epoch [ 688] L = 37.798663, acc = 0.860000\n",
      "epoch [ 689] L = 37.793742, acc = 0.860000\n",
      "epoch [ 690] L = 37.788785, acc = 0.860000\n",
      "epoch [ 691] L = 37.783790, acc = 0.860000\n",
      "epoch [ 692] L = 37.778759, acc = 0.860000\n",
      "epoch [ 693] L = 37.773690, acc = 0.860000\n",
      "epoch [ 694] L = 37.768583, acc = 0.860000\n",
      "epoch [ 695] L = 37.763438, acc = 0.860000\n",
      "epoch [ 696] L = 37.758255, acc = 0.860000\n",
      "epoch [ 697] L = 37.753033, acc = 0.860000\n",
      "epoch [ 698] L = 37.747772, acc = 0.860000\n",
      "epoch [ 699] L = 37.742472, acc = 0.860000\n",
      "epoch [ 700] L = 37.737132, acc = 0.860000\n",
      "epoch [ 701] L = 37.731752, acc = 0.860000\n",
      "epoch [ 702] L = 37.726332, acc = 0.860000\n",
      "epoch [ 703] L = 37.720871, acc = 0.860000\n",
      "epoch [ 704] L = 37.715369, acc = 0.860000\n",
      "epoch [ 705] L = 37.709825, acc = 0.860000\n",
      "epoch [ 706] L = 37.704240, acc = 0.860000\n",
      "epoch [ 707] L = 37.698613, acc = 0.860000\n",
      "epoch [ 708] L = 37.692944, acc = 0.860000\n",
      "epoch [ 709] L = 37.687232, acc = 0.860000\n",
      "epoch [ 710] L = 37.681477, acc = 0.860000\n",
      "epoch [ 711] L = 37.675679, acc = 0.860000\n",
      "epoch [ 712] L = 37.669836, acc = 0.860000\n",
      "epoch [ 713] L = 37.663950, acc = 0.860000\n",
      "epoch [ 714] L = 37.658020, acc = 0.860000\n",
      "epoch [ 715] L = 37.652044, acc = 0.860000\n",
      "epoch [ 716] L = 37.646024, acc = 0.860000\n",
      "epoch [ 717] L = 37.639958, acc = 0.860000\n",
      "epoch [ 718] L = 37.633846, acc = 0.860000\n",
      "epoch [ 719] L = 37.627688, acc = 0.860000\n",
      "epoch [ 720] L = 37.621483, acc = 0.860000\n",
      "epoch [ 721] L = 37.615231, acc = 0.860000\n",
      "epoch [ 722] L = 37.608933, acc = 0.860000\n",
      "epoch [ 723] L = 37.602586, acc = 0.860000\n",
      "epoch [ 724] L = 37.596192, acc = 0.860000\n",
      "epoch [ 725] L = 37.589749, acc = 0.860000\n",
      "epoch [ 726] L = 37.583257, acc = 0.860000\n",
      "epoch [ 727] L = 37.576716, acc = 0.860000\n",
      "epoch [ 728] L = 37.570126, acc = 0.860000\n",
      "epoch [ 729] L = 37.563486, acc = 0.860000\n",
      "epoch [ 730] L = 37.556796, acc = 0.860000\n",
      "epoch [ 731] L = 37.550055, acc = 0.860000\n",
      "epoch [ 732] L = 37.543263, acc = 0.860000\n",
      "epoch [ 733] L = 37.536420, acc = 0.860000\n",
      "epoch [ 734] L = 37.529525, acc = 0.860000\n",
      "epoch [ 735] L = 37.522578, acc = 0.860000\n",
      "epoch [ 736] L = 37.515579, acc = 0.860000\n",
      "epoch [ 737] L = 37.508526, acc = 0.860000\n",
      "epoch [ 738] L = 37.501421, acc = 0.860000\n",
      "epoch [ 739] L = 37.494262, acc = 0.860000\n",
      "epoch [ 740] L = 37.487049, acc = 0.860000\n",
      "epoch [ 741] L = 37.479781, acc = 0.860000\n",
      "epoch [ 742] L = 37.472459, acc = 0.860000\n",
      "epoch [ 743] L = 37.465081, acc = 0.860000\n",
      "epoch [ 744] L = 37.457648, acc = 0.860000\n",
      "epoch [ 745] L = 37.450159, acc = 0.860000\n",
      "epoch [ 746] L = 37.442614, acc = 0.860000\n",
      "epoch [ 747] L = 37.435012, acc = 0.860000\n",
      "epoch [ 748] L = 37.427353, acc = 0.860000\n",
      "epoch [ 749] L = 37.419637, acc = 0.865000\n",
      "epoch [ 750] L = 37.411862, acc = 0.865000\n",
      "epoch [ 751] L = 37.404030, acc = 0.865000\n",
      "epoch [ 752] L = 37.396139, acc = 0.865000\n",
      "epoch [ 753] L = 37.388189, acc = 0.865000\n",
      "epoch [ 754] L = 37.380179, acc = 0.865000\n",
      "epoch [ 755] L = 37.372110, acc = 0.865000\n",
      "epoch [ 756] L = 37.363980, acc = 0.865000\n",
      "epoch [ 757] L = 37.355790, acc = 0.865000\n",
      "epoch [ 758] L = 37.347539, acc = 0.865000\n",
      "epoch [ 759] L = 37.339227, acc = 0.865000\n",
      "epoch [ 760] L = 37.330853, acc = 0.865000\n",
      "epoch [ 761] L = 37.322417, acc = 0.865000\n",
      "epoch [ 762] L = 37.313919, acc = 0.865000\n",
      "epoch [ 763] L = 37.305358, acc = 0.865000\n",
      "epoch [ 764] L = 37.296733, acc = 0.865000\n",
      "epoch [ 765] L = 37.288045, acc = 0.865000\n",
      "epoch [ 766] L = 37.279293, acc = 0.865000\n",
      "epoch [ 767] L = 37.270477, acc = 0.865000\n",
      "epoch [ 768] L = 37.261595, acc = 0.865000\n",
      "epoch [ 769] L = 37.252649, acc = 0.865000\n",
      "epoch [ 770] L = 37.243637, acc = 0.865000\n",
      "epoch [ 771] L = 37.234560, acc = 0.865000\n",
      "epoch [ 772] L = 37.225416, acc = 0.865000\n",
      "epoch [ 773] L = 37.216205, acc = 0.865000\n",
      "epoch [ 774] L = 37.206928, acc = 0.865000\n",
      "epoch [ 775] L = 37.197583, acc = 0.865000\n",
      "epoch [ 776] L = 37.188171, acc = 0.865000\n",
      "epoch [ 777] L = 37.178690, acc = 0.865000\n",
      "epoch [ 778] L = 37.169141, acc = 0.865000\n",
      "epoch [ 779] L = 37.159523, acc = 0.865000\n",
      "epoch [ 780] L = 37.149836, acc = 0.865000\n",
      "epoch [ 781] L = 37.140080, acc = 0.865000\n",
      "epoch [ 782] L = 37.130254, acc = 0.865000\n",
      "epoch [ 783] L = 37.120357, acc = 0.865000\n",
      "epoch [ 784] L = 37.110390, acc = 0.865000\n",
      "epoch [ 785] L = 37.100352, acc = 0.865000\n",
      "epoch [ 786] L = 37.090243, acc = 0.865000\n",
      "epoch [ 787] L = 37.080062, acc = 0.865000\n",
      "epoch [ 788] L = 37.069809, acc = 0.865000\n",
      "epoch [ 789] L = 37.059483, acc = 0.865000\n",
      "epoch [ 790] L = 37.049086, acc = 0.865000\n",
      "epoch [ 791] L = 37.038615, acc = 0.865000\n",
      "epoch [ 792] L = 37.028071, acc = 0.865000\n",
      "epoch [ 793] L = 37.017453, acc = 0.865000\n",
      "epoch [ 794] L = 37.006761, acc = 0.865000\n",
      "epoch [ 795] L = 36.995996, acc = 0.865000\n",
      "epoch [ 796] L = 36.985155, acc = 0.865000\n",
      "epoch [ 797] L = 36.974240, acc = 0.865000\n",
      "epoch [ 798] L = 36.963249, acc = 0.865000\n",
      "epoch [ 799] L = 36.952183, acc = 0.865000\n",
      "epoch [ 800] L = 36.941041, acc = 0.865000\n",
      "epoch [ 801] L = 36.929823, acc = 0.865000\n",
      "epoch [ 802] L = 36.918529, acc = 0.865000\n",
      "epoch [ 803] L = 36.907158, acc = 0.865000\n",
      "epoch [ 804] L = 36.895709, acc = 0.865000\n",
      "epoch [ 805] L = 36.884184, acc = 0.865000\n",
      "epoch [ 806] L = 36.872581, acc = 0.865000\n",
      "epoch [ 807] L = 36.860900, acc = 0.865000\n",
      "epoch [ 808] L = 36.849141, acc = 0.865000\n",
      "epoch [ 809] L = 36.837304, acc = 0.870000\n",
      "epoch [ 810] L = 36.825388, acc = 0.870000\n",
      "epoch [ 811] L = 36.813393, acc = 0.870000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch [ 812] L = 36.801319, acc = 0.870000\n",
      "epoch [ 813] L = 36.789166, acc = 0.870000\n",
      "epoch [ 814] L = 36.776933, acc = 0.870000\n",
      "epoch [ 815] L = 36.764620, acc = 0.870000\n",
      "epoch [ 816] L = 36.752227, acc = 0.870000\n",
      "epoch [ 817] L = 36.739753, acc = 0.870000\n",
      "epoch [ 818] L = 36.727199, acc = 0.870000\n",
      "epoch [ 819] L = 36.714565, acc = 0.870000\n",
      "epoch [ 820] L = 36.701849, acc = 0.870000\n",
      "epoch [ 821] L = 36.689052, acc = 0.870000\n",
      "epoch [ 822] L = 36.676173, acc = 0.870000\n",
      "epoch [ 823] L = 36.663213, acc = 0.870000\n",
      "epoch [ 824] L = 36.650171, acc = 0.870000\n",
      "epoch [ 825] L = 36.637047, acc = 0.870000\n",
      "epoch [ 826] L = 36.623840, acc = 0.870000\n",
      "epoch [ 827] L = 36.610552, acc = 0.870000\n",
      "epoch [ 828] L = 36.597180, acc = 0.870000\n",
      "epoch [ 829] L = 36.583726, acc = 0.870000\n",
      "epoch [ 830] L = 36.570189, acc = 0.870000\n",
      "epoch [ 831] L = 36.556569, acc = 0.870000\n",
      "epoch [ 832] L = 36.542866, acc = 0.870000\n",
      "epoch [ 833] L = 36.529080, acc = 0.870000\n",
      "epoch [ 834] L = 36.515209, acc = 0.870000\n",
      "epoch [ 835] L = 36.501256, acc = 0.870000\n",
      "epoch [ 836] L = 36.487218, acc = 0.870000\n",
      "epoch [ 837] L = 36.473097, acc = 0.875000\n",
      "epoch [ 838] L = 36.458891, acc = 0.875000\n",
      "epoch [ 839] L = 36.444602, acc = 0.875000\n",
      "epoch [ 840] L = 36.430228, acc = 0.875000\n",
      "epoch [ 841] L = 36.415770, acc = 0.875000\n",
      "epoch [ 842] L = 36.401228, acc = 0.875000\n",
      "epoch [ 843] L = 36.386601, acc = 0.875000\n",
      "epoch [ 844] L = 36.371889, acc = 0.875000\n",
      "epoch [ 845] L = 36.357093, acc = 0.875000\n",
      "epoch [ 846] L = 36.342212, acc = 0.875000\n",
      "epoch [ 847] L = 36.327247, acc = 0.875000\n",
      "epoch [ 848] L = 36.312196, acc = 0.875000\n",
      "epoch [ 849] L = 36.297061, acc = 0.875000\n",
      "epoch [ 850] L = 36.281841, acc = 0.875000\n",
      "epoch [ 851] L = 36.266536, acc = 0.875000\n",
      "epoch [ 852] L = 36.251146, acc = 0.875000\n",
      "epoch [ 853] L = 36.235670, acc = 0.875000\n",
      "epoch [ 854] L = 36.220110, acc = 0.875000\n",
      "epoch [ 855] L = 36.204465, acc = 0.875000\n",
      "epoch [ 856] L = 36.188735, acc = 0.875000\n",
      "epoch [ 857] L = 36.172920, acc = 0.875000\n",
      "epoch [ 858] L = 36.157020, acc = 0.875000\n",
      "epoch [ 859] L = 36.141035, acc = 0.875000\n",
      "epoch [ 860] L = 36.124965, acc = 0.875000\n",
      "epoch [ 861] L = 36.108810, acc = 0.875000\n",
      "epoch [ 862] L = 36.092570, acc = 0.875000\n",
      "epoch [ 863] L = 36.076245, acc = 0.875000\n",
      "epoch [ 864] L = 36.059835, acc = 0.875000\n",
      "epoch [ 865] L = 36.043341, acc = 0.875000\n",
      "epoch [ 866] L = 36.026762, acc = 0.875000\n",
      "epoch [ 867] L = 36.010099, acc = 0.875000\n",
      "epoch [ 868] L = 35.993351, acc = 0.875000\n",
      "epoch [ 869] L = 35.976519, acc = 0.875000\n",
      "epoch [ 870] L = 35.959602, acc = 0.875000\n",
      "epoch [ 871] L = 35.942601, acc = 0.875000\n",
      "epoch [ 872] L = 35.925516, acc = 0.875000\n",
      "epoch [ 873] L = 35.908347, acc = 0.875000\n",
      "epoch [ 874] L = 35.891094, acc = 0.875000\n",
      "epoch [ 875] L = 35.873757, acc = 0.875000\n",
      "epoch [ 876] L = 35.856337, acc = 0.880000\n",
      "epoch [ 877] L = 35.838833, acc = 0.880000\n",
      "epoch [ 878] L = 35.821245, acc = 0.880000\n",
      "epoch [ 879] L = 35.803575, acc = 0.880000\n",
      "epoch [ 880] L = 35.785822, acc = 0.880000\n",
      "epoch [ 881] L = 35.767985, acc = 0.880000\n",
      "epoch [ 882] L = 35.750066, acc = 0.880000\n",
      "epoch [ 883] L = 35.732065, acc = 0.880000\n",
      "epoch [ 884] L = 35.713981, acc = 0.880000\n",
      "epoch [ 885] L = 35.695814, acc = 0.880000\n",
      "epoch [ 886] L = 35.677566, acc = 0.880000\n",
      "epoch [ 887] L = 35.659237, acc = 0.880000\n",
      "epoch [ 888] L = 35.640825, acc = 0.880000\n",
      "epoch [ 889] L = 35.622332, acc = 0.880000\n",
      "epoch [ 890] L = 35.603759, acc = 0.880000\n",
      "epoch [ 891] L = 35.585104, acc = 0.880000\n",
      "epoch [ 892] L = 35.566369, acc = 0.880000\n",
      "epoch [ 893] L = 35.547553, acc = 0.880000\n",
      "epoch [ 894] L = 35.528657, acc = 0.880000\n",
      "epoch [ 895] L = 35.509681, acc = 0.880000\n",
      "epoch [ 896] L = 35.490626, acc = 0.880000\n",
      "epoch [ 897] L = 35.471491, acc = 0.880000\n",
      "epoch [ 898] L = 35.452277, acc = 0.880000\n",
      "epoch [ 899] L = 35.432984, acc = 0.880000\n",
      "epoch [ 900] L = 35.413612, acc = 0.880000\n",
      "epoch [ 901] L = 35.394163, acc = 0.880000\n",
      "epoch [ 902] L = 35.374635, acc = 0.880000\n",
      "epoch [ 903] L = 35.355030, acc = 0.880000\n",
      "epoch [ 904] L = 35.335347, acc = 0.880000\n",
      "epoch [ 905] L = 35.315587, acc = 0.880000\n",
      "epoch [ 906] L = 35.295751, acc = 0.880000\n",
      "epoch [ 907] L = 35.275838, acc = 0.880000\n",
      "epoch [ 908] L = 35.255848, acc = 0.880000\n",
      "epoch [ 909] L = 35.235784, acc = 0.880000\n",
      "epoch [ 910] L = 35.215643, acc = 0.880000\n",
      "epoch [ 911] L = 35.195428, acc = 0.880000\n",
      "epoch [ 912] L = 35.175137, acc = 0.880000\n",
      "epoch [ 913] L = 35.154773, acc = 0.880000\n",
      "epoch [ 914] L = 35.134334, acc = 0.880000\n",
      "epoch [ 915] L = 35.113822, acc = 0.880000\n",
      "epoch [ 916] L = 35.093236, acc = 0.880000\n",
      "epoch [ 917] L = 35.072578, acc = 0.880000\n",
      "epoch [ 918] L = 35.051846, acc = 0.880000\n",
      "epoch [ 919] L = 35.031043, acc = 0.880000\n",
      "epoch [ 920] L = 35.010168, acc = 0.880000\n",
      "epoch [ 921] L = 34.989221, acc = 0.880000\n",
      "epoch [ 922] L = 34.968203, acc = 0.880000\n",
      "epoch [ 923] L = 34.947115, acc = 0.880000\n",
      "epoch [ 924] L = 34.925956, acc = 0.880000\n",
      "epoch [ 925] L = 34.904728, acc = 0.880000\n",
      "epoch [ 926] L = 34.883430, acc = 0.880000\n",
      "epoch [ 927] L = 34.862064, acc = 0.880000\n",
      "epoch [ 928] L = 34.840628, acc = 0.880000\n",
      "epoch [ 929] L = 34.819125, acc = 0.880000\n",
      "epoch [ 930] L = 34.797554, acc = 0.880000\n",
      "epoch [ 931] L = 34.775915, acc = 0.880000\n",
      "epoch [ 932] L = 34.754210, acc = 0.880000\n",
      "epoch [ 933] L = 34.732438, acc = 0.880000\n",
      "epoch [ 934] L = 34.710600, acc = 0.880000\n",
      "epoch [ 935] L = 34.688697, acc = 0.880000\n",
      "epoch [ 936] L = 34.666729, acc = 0.880000\n",
      "epoch [ 937] L = 34.644696, acc = 0.885000\n",
      "epoch [ 938] L = 34.622598, acc = 0.885000\n",
      "epoch [ 939] L = 34.600438, acc = 0.885000\n",
      "epoch [ 940] L = 34.578213, acc = 0.885000\n",
      "epoch [ 941] L = 34.555927, acc = 0.885000\n",
      "epoch [ 942] L = 34.533577, acc = 0.885000\n",
      "epoch [ 943] L = 34.511166, acc = 0.885000\n",
      "epoch [ 944] L = 34.488694, acc = 0.885000\n",
      "epoch [ 945] L = 34.466161, acc = 0.885000\n",
      "epoch [ 946] L = 34.443567, acc = 0.885000\n",
      "epoch [ 947] L = 34.420913, acc = 0.885000\n",
      "epoch [ 948] L = 34.398200, acc = 0.885000\n",
      "epoch [ 949] L = 34.375428, acc = 0.885000\n",
      "epoch [ 950] L = 34.352598, acc = 0.885000\n",
      "epoch [ 951] L = 34.329710, acc = 0.885000\n",
      "epoch [ 952] L = 34.306764, acc = 0.885000\n",
      "epoch [ 953] L = 34.283761, acc = 0.885000\n",
      "epoch [ 954] L = 34.260702, acc = 0.885000\n",
      "epoch [ 955] L = 34.237587, acc = 0.885000\n",
      "epoch [ 956] L = 34.214416, acc = 0.885000\n",
      "epoch [ 957] L = 34.191190, acc = 0.885000\n",
      "epoch [ 958] L = 34.167910, acc = 0.885000\n",
      "epoch [ 959] L = 34.144576, acc = 0.885000\n",
      "epoch [ 960] L = 34.121189, acc = 0.885000\n",
      "epoch [ 961] L = 34.097749, acc = 0.885000\n",
      "epoch [ 962] L = 34.074256, acc = 0.885000\n",
      "epoch [ 963] L = 34.050712, acc = 0.885000\n",
      "epoch [ 964] L = 34.027116, acc = 0.885000\n",
      "epoch [ 965] L = 34.003469, acc = 0.885000\n",
      "epoch [ 966] L = 33.979773, acc = 0.885000\n",
      "epoch [ 967] L = 33.956026, acc = 0.885000\n",
      "epoch [ 968] L = 33.932230, acc = 0.885000\n",
      "epoch [ 969] L = 33.908386, acc = 0.885000\n",
      "epoch [ 970] L = 33.884493, acc = 0.890000\n",
      "epoch [ 971] L = 33.860552, acc = 0.890000\n",
      "epoch [ 972] L = 33.836565, acc = 0.890000\n",
      "epoch [ 973] L = 33.812531, acc = 0.890000\n",
      "epoch [ 974] L = 33.788451, acc = 0.890000\n",
      "epoch [ 975] L = 33.764325, acc = 0.890000\n",
      "epoch [ 976] L = 33.740155, acc = 0.890000\n",
      "epoch [ 977] L = 33.715940, acc = 0.890000\n",
      "epoch [ 978] L = 33.691681, acc = 0.890000\n",
      "epoch [ 979] L = 33.667378, acc = 0.890000\n",
      "epoch [ 980] L = 33.643033, acc = 0.890000\n",
      "epoch [ 981] L = 33.618646, acc = 0.890000\n",
      "epoch [ 982] L = 33.594216, acc = 0.890000\n",
      "epoch [ 983] L = 33.569746, acc = 0.895000\n",
      "epoch [ 984] L = 33.545235, acc = 0.895000\n",
      "epoch [ 985] L = 33.520684, acc = 0.895000\n",
      "epoch [ 986] L = 33.496093, acc = 0.895000\n",
      "epoch [ 987] L = 33.471463, acc = 0.895000\n",
      "epoch [ 988] L = 33.446795, acc = 0.895000\n",
      "epoch [ 989] L = 33.422088, acc = 0.895000\n",
      "epoch [ 990] L = 33.397344, acc = 0.895000\n",
      "epoch [ 991] L = 33.372564, acc = 0.895000\n",
      "epoch [ 992] L = 33.347747, acc = 0.895000\n",
      "epoch [ 993] L = 33.322894, acc = 0.895000\n",
      "epoch [ 994] L = 33.298006, acc = 0.895000\n",
      "epoch [ 995] L = 33.273083, acc = 0.895000\n",
      "epoch [ 996] L = 33.248126, acc = 0.895000\n",
      "epoch [ 997] L = 33.223135, acc = 0.895000\n",
      "epoch [ 998] L = 33.198111, acc = 0.895000\n",
      "epoch [ 999] L = 33.173055, acc = 0.895000\n",
      "epoch [1000] L = 33.147966, acc = 0.895000\n",
      "epoch [1001] L = 33.122846, acc = 0.895000\n",
      "epoch [1002] L = 33.097695, acc = 0.895000\n",
      "epoch [1003] L = 33.072514, acc = 0.895000\n",
      "epoch [1004] L = 33.047302, acc = 0.895000\n",
      "epoch [1005] L = 33.022062, acc = 0.895000\n",
      "epoch [1006] L = 32.996792, acc = 0.895000\n",
      "epoch [1007] L = 32.971495, acc = 0.895000\n",
      "epoch [1008] L = 32.946169, acc = 0.895000\n",
      "epoch [1009] L = 32.920816, acc = 0.895000\n",
      "epoch [1010] L = 32.895437, acc = 0.895000\n",
      "epoch [1011] L = 32.870031, acc = 0.895000\n",
      "epoch [1012] L = 32.844600, acc = 0.895000\n",
      "epoch [1013] L = 32.819143, acc = 0.895000\n",
      "epoch [1014] L = 32.793662, acc = 0.895000\n",
      "epoch [1015] L = 32.768157, acc = 0.895000\n",
      "epoch [1016] L = 32.742628, acc = 0.895000\n",
      "epoch [1017] L = 32.717076, acc = 0.895000\n",
      "epoch [1018] L = 32.691502, acc = 0.895000\n",
      "epoch [1019] L = 32.665906, acc = 0.895000\n",
      "epoch [1020] L = 32.640288, acc = 0.895000\n",
      "epoch [1021] L = 32.614649, acc = 0.900000\n",
      "epoch [1022] L = 32.588990, acc = 0.900000\n",
      "epoch [1023] L = 32.563311, acc = 0.900000\n",
      "epoch [1024] L = 32.537613, acc = 0.900000\n",
      "epoch [1025] L = 32.511895, acc = 0.900000\n",
      "epoch [1026] L = 32.486159, acc = 0.900000\n",
      "epoch [1027] L = 32.460405, acc = 0.900000\n",
      "epoch [1028] L = 32.434634, acc = 0.900000\n",
      "epoch [1029] L = 32.408846, acc = 0.900000\n",
      "epoch [1030] L = 32.383041, acc = 0.900000\n",
      "epoch [1031] L = 32.357221, acc = 0.900000\n",
      "epoch [1032] L = 32.331385, acc = 0.900000\n",
      "epoch [1033] L = 32.305534, acc = 0.900000\n",
      "epoch [1034] L = 32.279669, acc = 0.900000\n",
      "epoch [1035] L = 32.253790, acc = 0.900000\n",
      "epoch [1036] L = 32.227897, acc = 0.900000\n",
      "epoch [1037] L = 32.201992, acc = 0.900000\n",
      "epoch [1038] L = 32.176074, acc = 0.900000\n",
      "epoch [1039] L = 32.150144, acc = 0.900000\n",
      "epoch [1040] L = 32.124202, acc = 0.900000\n",
      "epoch [1041] L = 32.098249, acc = 0.900000\n",
      "epoch [1042] L = 32.072286, acc = 0.900000\n",
      "epoch [1043] L = 32.046313, acc = 0.900000\n",
      "epoch [1044] L = 32.020330, acc = 0.900000\n",
      "epoch [1045] L = 31.994338, acc = 0.900000\n",
      "epoch [1046] L = 31.968337, acc = 0.900000\n",
      "epoch [1047] L = 31.942328, acc = 0.900000\n",
      "epoch [1048] L = 31.916311, acc = 0.900000\n",
      "epoch [1049] L = 31.890287, acc = 0.900000\n",
      "epoch [1050] L = 31.864256, acc = 0.900000\n",
      "epoch [1051] L = 31.838219, acc = 0.900000\n",
      "epoch [1052] L = 31.812176, acc = 0.900000\n",
      "epoch [1053] L = 31.786127, acc = 0.900000\n",
      "epoch [1054] L = 31.760073, acc = 0.900000\n",
      "epoch [1055] L = 31.734015, acc = 0.900000\n",
      "epoch [1056] L = 31.707953, acc = 0.900000\n",
      "epoch [1057] L = 31.681886, acc = 0.900000\n",
      "epoch [1058] L = 31.655817, acc = 0.900000\n",
      "epoch [1059] L = 31.629744, acc = 0.900000\n",
      "epoch [1060] L = 31.603670, acc = 0.900000\n",
      "epoch [1061] L = 31.577593, acc = 0.900000\n",
      "epoch [1062] L = 31.551514, acc = 0.900000\n",
      "epoch [1063] L = 31.525435, acc = 0.900000\n",
      "epoch [1064] L = 31.499355, acc = 0.900000\n",
      "epoch [1065] L = 31.473274, acc = 0.900000\n",
      "epoch [1066] L = 31.447194, acc = 0.900000\n",
      "epoch [1067] L = 31.421114, acc = 0.900000\n",
      "epoch [1068] L = 31.395035, acc = 0.900000\n",
      "epoch [1069] L = 31.368957, acc = 0.900000\n",
      "epoch [1070] L = 31.342881, acc = 0.900000\n",
      "epoch [1071] L = 31.316808, acc = 0.900000\n",
      "epoch [1072] L = 31.290737, acc = 0.900000\n",
      "epoch [1073] L = 31.264668, acc = 0.900000\n",
      "epoch [1074] L = 31.238603, acc = 0.900000\n",
      "epoch [1075] L = 31.212542, acc = 0.900000\n",
      "epoch [1076] L = 31.186485, acc = 0.900000\n",
      "epoch [1077] L = 31.160433, acc = 0.900000\n",
      "epoch [1078] L = 31.134385, acc = 0.900000\n",
      "epoch [1079] L = 31.108343, acc = 0.900000\n",
      "epoch [1080] L = 31.082306, acc = 0.900000\n",
      "epoch [1081] L = 31.056275, acc = 0.900000\n",
      "epoch [1082] L = 31.030251, acc = 0.900000\n",
      "epoch [1083] L = 31.004233, acc = 0.900000\n",
      "epoch [1084] L = 30.978223, acc = 0.900000\n",
      "epoch [1085] L = 30.952220, acc = 0.900000\n",
      "epoch [1086] L = 30.926224, acc = 0.900000\n",
      "epoch [1087] L = 30.900237, acc = 0.900000\n",
      "epoch [1088] L = 30.874259, acc = 0.900000\n",
      "epoch [1089] L = 30.848289, acc = 0.900000\n",
      "epoch [1090] L = 30.822329, acc = 0.900000\n",
      "epoch [1091] L = 30.796378, acc = 0.900000\n",
      "epoch [1092] L = 30.770437, acc = 0.900000\n",
      "epoch [1093] L = 30.744507, acc = 0.900000\n",
      "epoch [1094] L = 30.718587, acc = 0.900000\n",
      "epoch [1095] L = 30.692678, acc = 0.900000\n",
      "epoch [1096] L = 30.666780, acc = 0.900000\n",
      "epoch [1097] L = 30.640894, acc = 0.900000\n",
      "epoch [1098] L = 30.615020, acc = 0.900000\n",
      "epoch [1099] L = 30.589158, acc = 0.900000\n",
      "epoch [1100] L = 30.563308, acc = 0.900000\n",
      "epoch [1101] L = 30.537472, acc = 0.900000\n",
      "epoch [1102] L = 30.511649, acc = 0.905000\n",
      "epoch [1103] L = 30.485839, acc = 0.905000\n",
      "epoch [1104] L = 30.460043, acc = 0.905000\n",
      "epoch [1105] L = 30.434261, acc = 0.905000\n",
      "epoch [1106] L = 30.408493, acc = 0.905000\n",
      "epoch [1107] L = 30.382740, acc = 0.905000\n",
      "epoch [1108] L = 30.357002, acc = 0.905000\n",
      "epoch [1109] L = 30.331280, acc = 0.905000\n",
      "epoch [1110] L = 30.305573, acc = 0.905000\n",
      "epoch [1111] L = 30.279882, acc = 0.905000\n",
      "epoch [1112] L = 30.254207, acc = 0.905000\n",
      "epoch [1113] L = 30.228548, acc = 0.905000\n",
      "epoch [1114] L = 30.202907, acc = 0.905000\n",
      "epoch [1115] L = 30.177282, acc = 0.905000\n",
      "epoch [1116] L = 30.151674, acc = 0.905000\n",
      "epoch [1117] L = 30.126084, acc = 0.905000\n",
      "epoch [1118] L = 30.100512, acc = 0.905000\n",
      "epoch [1119] L = 30.074958, acc = 0.905000\n",
      "epoch [1120] L = 30.049422, acc = 0.905000\n",
      "epoch [1121] L = 30.023905, acc = 0.910000\n",
      "epoch [1122] L = 29.998407, acc = 0.910000\n",
      "epoch [1123] L = 29.972928, acc = 0.910000\n",
      "epoch [1124] L = 29.947468, acc = 0.910000\n",
      "epoch [1125] L = 29.922027, acc = 0.910000\n",
      "epoch [1126] L = 29.896607, acc = 0.910000\n",
      "epoch [1127] L = 29.871207, acc = 0.910000\n",
      "epoch [1128] L = 29.845826, acc = 0.910000\n",
      "epoch [1129] L = 29.820467, acc = 0.910000\n",
      "epoch [1130] L = 29.795128, acc = 0.910000\n",
      "epoch [1131] L = 29.769811, acc = 0.915000\n",
      "epoch [1132] L = 29.744514, acc = 0.915000\n",
      "epoch [1133] L = 29.719239, acc = 0.915000\n",
      "epoch [1134] L = 29.693986, acc = 0.915000\n",
      "epoch [1135] L = 29.668755, acc = 0.915000\n",
      "epoch [1136] L = 29.643546, acc = 0.915000\n",
      "epoch [1137] L = 29.618359, acc = 0.915000\n",
      "epoch [1138] L = 29.593194, acc = 0.915000\n",
      "epoch [1139] L = 29.568053, acc = 0.915000\n",
      "epoch [1140] L = 29.542935, acc = 0.915000\n",
      "epoch [1141] L = 29.517839, acc = 0.915000\n",
      "epoch [1142] L = 29.492767, acc = 0.915000\n",
      "epoch [1143] L = 29.467719, acc = 0.915000\n",
      "epoch [1144] L = 29.442695, acc = 0.915000\n",
      "epoch [1145] L = 29.417694, acc = 0.915000\n",
      "epoch [1146] L = 29.392718, acc = 0.915000\n",
      "epoch [1147] L = 29.367766, acc = 0.915000\n",
      "epoch [1148] L = 29.342839, acc = 0.915000\n",
      "epoch [1149] L = 29.317936, acc = 0.915000\n",
      "epoch [1150] L = 29.293059, acc = 0.915000\n",
      "epoch [1151] L = 29.268206, acc = 0.915000\n",
      "epoch [1152] L = 29.243379, acc = 0.915000\n",
      "epoch [1153] L = 29.218577, acc = 0.915000\n",
      "epoch [1154] L = 29.193801, acc = 0.915000\n",
      "epoch [1155] L = 29.169051, acc = 0.915000\n",
      "epoch [1156] L = 29.144326, acc = 0.915000\n",
      "epoch [1157] L = 29.119628, acc = 0.915000\n",
      "epoch [1158] L = 29.094956, acc = 0.915000\n",
      "epoch [1159] L = 29.070311, acc = 0.915000\n",
      "epoch [1160] L = 29.045692, acc = 0.915000\n",
      "epoch [1161] L = 29.021100, acc = 0.915000\n",
      "epoch [1162] L = 28.996535, acc = 0.915000\n",
      "epoch [1163] L = 28.971997, acc = 0.915000\n",
      "epoch [1164] L = 28.947487, acc = 0.915000\n",
      "epoch [1165] L = 28.923003, acc = 0.915000\n",
      "epoch [1166] L = 28.898548, acc = 0.915000\n",
      "epoch [1167] L = 28.874120, acc = 0.915000\n",
      "epoch [1168] L = 28.849720, acc = 0.915000\n",
      "epoch [1169] L = 28.825347, acc = 0.915000\n",
      "epoch [1170] L = 28.801003, acc = 0.915000\n",
      "epoch [1171] L = 28.776687, acc = 0.915000\n",
      "epoch [1172] L = 28.752400, acc = 0.915000\n",
      "epoch [1173] L = 28.728141, acc = 0.915000\n",
      "epoch [1174] L = 28.703911, acc = 0.915000\n",
      "epoch [1175] L = 28.679709, acc = 0.915000\n",
      "epoch [1176] L = 28.655536, acc = 0.915000\n",
      "epoch [1177] L = 28.631393, acc = 0.915000\n",
      "epoch [1178] L = 28.607278, acc = 0.915000\n",
      "epoch [1179] L = 28.583193, acc = 0.915000\n",
      "epoch [1180] L = 28.559137, acc = 0.915000\n",
      "epoch [1181] L = 28.535111, acc = 0.915000\n",
      "epoch [1182] L = 28.511114, acc = 0.915000\n",
      "epoch [1183] L = 28.487147, acc = 0.915000\n",
      "epoch [1184] L = 28.463209, acc = 0.915000\n",
      "epoch [1185] L = 28.439302, acc = 0.915000\n",
      "epoch [1186] L = 28.415425, acc = 0.915000\n",
      "epoch [1187] L = 28.391577, acc = 0.915000\n",
      "epoch [1188] L = 28.367760, acc = 0.915000\n",
      "epoch [1189] L = 28.343974, acc = 0.915000\n",
      "epoch [1190] L = 28.320218, acc = 0.915000\n",
      "epoch [1191] L = 28.296492, acc = 0.915000\n",
      "epoch [1192] L = 28.272797, acc = 0.915000\n",
      "epoch [1193] L = 28.249133, acc = 0.915000\n",
      "epoch [1194] L = 28.225499, acc = 0.915000\n",
      "epoch [1195] L = 28.201897, acc = 0.915000\n",
      "epoch [1196] L = 28.178325, acc = 0.915000\n",
      "epoch [1197] L = 28.154784, acc = 0.915000\n",
      "epoch [1198] L = 28.131275, acc = 0.915000\n",
      "epoch [1199] L = 28.107797, acc = 0.915000\n",
      "epoch [1200] L = 28.084350, acc = 0.915000\n",
      "epoch [1201] L = 28.060935, acc = 0.915000\n",
      "epoch [1202] L = 28.037551, acc = 0.915000\n",
      "epoch [1203] L = 28.014199, acc = 0.915000\n",
      "epoch [1204] L = 27.990878, acc = 0.915000\n",
      "epoch [1205] L = 27.967589, acc = 0.915000\n",
      "epoch [1206] L = 27.944331, acc = 0.915000\n",
      "epoch [1207] L = 27.921106, acc = 0.915000\n",
      "epoch [1208] L = 27.897913, acc = 0.915000\n",
      "epoch [1209] L = 27.874751, acc = 0.915000\n",
      "epoch [1210] L = 27.851622, acc = 0.915000\n",
      "epoch [1211] L = 27.828524, acc = 0.915000\n",
      "epoch [1212] L = 27.805459, acc = 0.915000\n",
      "epoch [1213] L = 27.782426, acc = 0.915000\n",
      "epoch [1214] L = 27.759425, acc = 0.915000\n",
      "epoch [1215] L = 27.736457, acc = 0.915000\n",
      "epoch [1216] L = 27.713521, acc = 0.915000\n",
      "epoch [1217] L = 27.690618, acc = 0.915000\n",
      "epoch [1218] L = 27.667747, acc = 0.915000\n",
      "epoch [1219] L = 27.644908, acc = 0.915000\n",
      "epoch [1220] L = 27.622102, acc = 0.915000\n",
      "epoch [1221] L = 27.599329, acc = 0.915000\n",
      "epoch [1222] L = 27.576589, acc = 0.915000\n",
      "epoch [1223] L = 27.553881, acc = 0.915000\n",
      "epoch [1224] L = 27.531206, acc = 0.915000\n",
      "epoch [1225] L = 27.508564, acc = 0.920000\n",
      "epoch [1226] L = 27.485955, acc = 0.925000\n",
      "epoch [1227] L = 27.463379, acc = 0.925000\n",
      "epoch [1228] L = 27.440836, acc = 0.925000\n",
      "epoch [1229] L = 27.418326, acc = 0.925000\n",
      "epoch [1230] L = 27.395849, acc = 0.925000\n",
      "epoch [1231] L = 27.373405, acc = 0.925000\n",
      "epoch [1232] L = 27.350994, acc = 0.925000\n",
      "epoch [1233] L = 27.328616, acc = 0.925000\n",
      "epoch [1234] L = 27.306271, acc = 0.925000\n",
      "epoch [1235] L = 27.283960, acc = 0.925000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch [1236] L = 27.261682, acc = 0.925000\n",
      "epoch [1237] L = 27.239437, acc = 0.925000\n",
      "epoch [1238] L = 27.217226, acc = 0.925000\n",
      "epoch [1239] L = 27.195047, acc = 0.925000\n",
      "epoch [1240] L = 27.172903, acc = 0.925000\n",
      "epoch [1241] L = 27.150791, acc = 0.925000\n",
      "epoch [1242] L = 27.128713, acc = 0.925000\n",
      "epoch [1243] L = 27.106669, acc = 0.925000\n",
      "epoch [1244] L = 27.084658, acc = 0.925000\n",
      "epoch [1245] L = 27.062680, acc = 0.925000\n",
      "epoch [1246] L = 27.040736, acc = 0.925000\n",
      "epoch [1247] L = 27.018825, acc = 0.925000\n",
      "epoch [1248] L = 26.996948, acc = 0.925000\n",
      "epoch [1249] L = 26.975105, acc = 0.925000\n",
      "epoch [1250] L = 26.953295, acc = 0.925000\n",
      "epoch [1251] L = 26.931519, acc = 0.925000\n",
      "epoch [1252] L = 26.909776, acc = 0.925000\n",
      "epoch [1253] L = 26.888067, acc = 0.925000\n",
      "epoch [1254] L = 26.866392, acc = 0.925000\n",
      "epoch [1255] L = 26.844750, acc = 0.930000\n",
      "epoch [1256] L = 26.823142, acc = 0.930000\n",
      "epoch [1257] L = 26.801567, acc = 0.930000\n",
      "epoch [1258] L = 26.780026, acc = 0.930000\n",
      "epoch [1259] L = 26.758519, acc = 0.930000\n",
      "epoch [1260] L = 26.737046, acc = 0.930000\n",
      "epoch [1261] L = 26.715606, acc = 0.930000\n",
      "epoch [1262] L = 26.694200, acc = 0.930000\n",
      "epoch [1263] L = 26.672827, acc = 0.930000\n",
      "epoch [1264] L = 26.651488, acc = 0.930000\n",
      "epoch [1265] L = 26.630184, acc = 0.930000\n",
      "epoch [1266] L = 26.608912, acc = 0.930000\n",
      "epoch [1267] L = 26.587675, acc = 0.930000\n",
      "epoch [1268] L = 26.566471, acc = 0.930000\n",
      "epoch [1269] L = 26.545301, acc = 0.930000\n",
      "epoch [1270] L = 26.524164, acc = 0.930000\n",
      "epoch [1271] L = 26.503061, acc = 0.930000\n",
      "epoch [1272] L = 26.481992, acc = 0.930000\n",
      "epoch [1273] L = 26.460957, acc = 0.930000\n",
      "epoch [1274] L = 26.439955, acc = 0.930000\n",
      "epoch [1275] L = 26.418987, acc = 0.930000\n",
      "epoch [1276] L = 26.398053, acc = 0.930000\n",
      "epoch [1277] L = 26.377153, acc = 0.930000\n",
      "epoch [1278] L = 26.356286, acc = 0.930000\n",
      "epoch [1279] L = 26.335452, acc = 0.930000\n",
      "epoch [1280] L = 26.314653, acc = 0.930000\n",
      "epoch [1281] L = 26.293887, acc = 0.930000\n",
      "epoch [1282] L = 26.273154, acc = 0.930000\n",
      "epoch [1283] L = 26.252456, acc = 0.930000\n",
      "epoch [1284] L = 26.231791, acc = 0.930000\n",
      "epoch [1285] L = 26.211159, acc = 0.930000\n",
      "epoch [1286] L = 26.190561, acc = 0.930000\n",
      "epoch [1287] L = 26.169997, acc = 0.930000\n",
      "epoch [1288] L = 26.149466, acc = 0.930000\n",
      "epoch [1289] L = 26.128969, acc = 0.930000\n",
      "epoch [1290] L = 26.108506, acc = 0.930000\n",
      "epoch [1291] L = 26.088075, acc = 0.930000\n",
      "epoch [1292] L = 26.067679, acc = 0.930000\n",
      "epoch [1293] L = 26.047316, acc = 0.930000\n",
      "epoch [1294] L = 26.026986, acc = 0.930000\n",
      "epoch [1295] L = 26.006690, acc = 0.930000\n",
      "epoch [1296] L = 25.986427, acc = 0.930000\n",
      "epoch [1297] L = 25.966198, acc = 0.930000\n",
      "epoch [1298] L = 25.946002, acc = 0.930000\n",
      "epoch [1299] L = 25.925839, acc = 0.930000\n",
      "epoch [1300] L = 25.905710, acc = 0.930000\n",
      "epoch [1301] L = 25.885615, acc = 0.930000\n",
      "epoch [1302] L = 25.865552, acc = 0.930000\n",
      "epoch [1303] L = 25.845523, acc = 0.930000\n",
      "epoch [1304] L = 25.825527, acc = 0.930000\n",
      "epoch [1305] L = 25.805564, acc = 0.930000\n",
      "epoch [1306] L = 25.785635, acc = 0.930000\n",
      "epoch [1307] L = 25.765739, acc = 0.930000\n",
      "epoch [1308] L = 25.745876, acc = 0.930000\n",
      "epoch [1309] L = 25.726046, acc = 0.930000\n",
      "epoch [1310] L = 25.706249, acc = 0.930000\n",
      "epoch [1311] L = 25.686485, acc = 0.930000\n",
      "epoch [1312] L = 25.666755, acc = 0.930000\n",
      "epoch [1313] L = 25.647058, acc = 0.930000\n",
      "epoch [1314] L = 25.627393, acc = 0.930000\n",
      "epoch [1315] L = 25.607762, acc = 0.930000\n",
      "epoch [1316] L = 25.588163, acc = 0.930000\n",
      "epoch [1317] L = 25.568598, acc = 0.930000\n",
      "epoch [1318] L = 25.549065, acc = 0.930000\n",
      "epoch [1319] L = 25.529566, acc = 0.930000\n",
      "epoch [1320] L = 25.510099, acc = 0.930000\n",
      "epoch [1321] L = 25.490665, acc = 0.930000\n",
      "epoch [1322] L = 25.471264, acc = 0.930000\n",
      "epoch [1323] L = 25.451896, acc = 0.930000\n",
      "epoch [1324] L = 25.432560, acc = 0.930000\n",
      "epoch [1325] L = 25.413257, acc = 0.930000\n",
      "epoch [1326] L = 25.393987, acc = 0.930000\n",
      "epoch [1327] L = 25.374749, acc = 0.930000\n",
      "epoch [1328] L = 25.355545, acc = 0.930000\n",
      "epoch [1329] L = 25.336372, acc = 0.930000\n",
      "epoch [1330] L = 25.317233, acc = 0.930000\n",
      "epoch [1331] L = 25.298125, acc = 0.930000\n",
      "epoch [1332] L = 25.279051, acc = 0.930000\n",
      "epoch [1333] L = 25.260008, acc = 0.930000\n",
      "epoch [1334] L = 25.240999, acc = 0.930000\n",
      "epoch [1335] L = 25.222021, acc = 0.930000\n",
      "epoch [1336] L = 25.203076, acc = 0.930000\n",
      "epoch [1337] L = 25.184164, acc = 0.930000\n",
      "epoch [1338] L = 25.165283, acc = 0.930000\n",
      "epoch [1339] L = 25.146435, acc = 0.930000\n",
      "epoch [1340] L = 25.127619, acc = 0.930000\n",
      "epoch [1341] L = 25.108835, acc = 0.930000\n",
      "epoch [1342] L = 25.090084, acc = 0.930000\n",
      "epoch [1343] L = 25.071364, acc = 0.930000\n",
      "epoch [1344] L = 25.052677, acc = 0.930000\n",
      "epoch [1345] L = 25.034022, acc = 0.930000\n",
      "epoch [1346] L = 25.015398, acc = 0.930000\n",
      "epoch [1347] L = 24.996807, acc = 0.930000\n",
      "epoch [1348] L = 24.978248, acc = 0.930000\n",
      "epoch [1349] L = 24.959720, acc = 0.930000\n",
      "epoch [1350] L = 24.941225, acc = 0.930000\n",
      "epoch [1351] L = 24.922761, acc = 0.930000\n",
      "epoch [1352] L = 24.904329, acc = 0.930000\n",
      "epoch [1353] L = 24.885929, acc = 0.930000\n",
      "epoch [1354] L = 24.867560, acc = 0.930000\n",
      "epoch [1355] L = 24.849223, acc = 0.930000\n",
      "epoch [1356] L = 24.830918, acc = 0.930000\n",
      "epoch [1357] L = 24.812644, acc = 0.930000\n",
      "epoch [1358] L = 24.794402, acc = 0.930000\n",
      "epoch [1359] L = 24.776191, acc = 0.930000\n",
      "epoch [1360] L = 24.758012, acc = 0.930000\n",
      "epoch [1361] L = 24.739865, acc = 0.930000\n",
      "epoch [1362] L = 24.721748, acc = 0.930000\n",
      "epoch [1363] L = 24.703663, acc = 0.930000\n",
      "epoch [1364] L = 24.685610, acc = 0.930000\n",
      "epoch [1365] L = 24.667587, acc = 0.930000\n",
      "epoch [1366] L = 24.649596, acc = 0.930000\n",
      "epoch [1367] L = 24.631636, acc = 0.930000\n",
      "epoch [1368] L = 24.613707, acc = 0.930000\n",
      "epoch [1369] L = 24.595810, acc = 0.930000\n",
      "epoch [1370] L = 24.577943, acc = 0.930000\n",
      "epoch [1371] L = 24.560107, acc = 0.930000\n",
      "epoch [1372] L = 24.542303, acc = 0.930000\n",
      "epoch [1373] L = 24.524529, acc = 0.930000\n",
      "epoch [1374] L = 24.506786, acc = 0.930000\n",
      "epoch [1375] L = 24.489074, acc = 0.930000\n",
      "epoch [1376] L = 24.471393, acc = 0.930000\n",
      "epoch [1377] L = 24.453743, acc = 0.930000\n",
      "epoch [1378] L = 24.436123, acc = 0.930000\n",
      "epoch [1379] L = 24.418534, acc = 0.930000\n",
      "epoch [1380] L = 24.400976, acc = 0.930000\n",
      "epoch [1381] L = 24.383448, acc = 0.930000\n",
      "epoch [1382] L = 24.365951, acc = 0.930000\n",
      "epoch [1383] L = 24.348484, acc = 0.930000\n",
      "epoch [1384] L = 24.331048, acc = 0.930000\n",
      "epoch [1385] L = 24.313642, acc = 0.930000\n",
      "epoch [1386] L = 24.296267, acc = 0.930000\n",
      "epoch [1387] L = 24.278922, acc = 0.930000\n",
      "epoch [1388] L = 24.261607, acc = 0.930000\n",
      "epoch [1389] L = 24.244323, acc = 0.930000\n",
      "epoch [1390] L = 24.227068, acc = 0.930000\n",
      "epoch [1391] L = 24.209844, acc = 0.930000\n",
      "epoch [1392] L = 24.192650, acc = 0.930000\n",
      "epoch [1393] L = 24.175486, acc = 0.930000\n",
      "epoch [1394] L = 24.158352, acc = 0.930000\n",
      "epoch [1395] L = 24.141248, acc = 0.930000\n",
      "epoch [1396] L = 24.124174, acc = 0.930000\n",
      "epoch [1397] L = 24.107130, acc = 0.930000\n",
      "epoch [1398] L = 24.090116, acc = 0.930000\n",
      "epoch [1399] L = 24.073131, acc = 0.930000\n",
      "epoch [1400] L = 24.056177, acc = 0.930000\n",
      "epoch [1401] L = 24.039252, acc = 0.930000\n",
      "epoch [1402] L = 24.022356, acc = 0.930000\n",
      "epoch [1403] L = 24.005491, acc = 0.930000\n",
      "epoch [1404] L = 23.988655, acc = 0.930000\n",
      "epoch [1405] L = 23.971848, acc = 0.930000\n",
      "epoch [1406] L = 23.955071, acc = 0.930000\n",
      "epoch [1407] L = 23.938323, acc = 0.930000\n",
      "epoch [1408] L = 23.921605, acc = 0.930000\n",
      "epoch [1409] L = 23.904916, acc = 0.930000\n",
      "epoch [1410] L = 23.888256, acc = 0.930000\n",
      "epoch [1411] L = 23.871626, acc = 0.930000\n",
      "epoch [1412] L = 23.855025, acc = 0.930000\n",
      "epoch [1413] L = 23.838453, acc = 0.930000\n",
      "epoch [1414] L = 23.821910, acc = 0.930000\n",
      "epoch [1415] L = 23.805396, acc = 0.930000\n",
      "epoch [1416] L = 23.788911, acc = 0.930000\n",
      "epoch [1417] L = 23.772455, acc = 0.930000\n",
      "epoch [1418] L = 23.756028, acc = 0.930000\n",
      "epoch [1419] L = 23.739630, acc = 0.930000\n",
      "epoch [1420] L = 23.723261, acc = 0.930000\n",
      "epoch [1421] L = 23.706921, acc = 0.930000\n",
      "epoch [1422] L = 23.690609, acc = 0.930000\n",
      "epoch [1423] L = 23.674326, acc = 0.930000\n",
      "epoch [1424] L = 23.658072, acc = 0.930000\n",
      "epoch [1425] L = 23.641846, acc = 0.930000\n",
      "epoch [1426] L = 23.625649, acc = 0.930000\n",
      "epoch [1427] L = 23.609480, acc = 0.930000\n",
      "epoch [1428] L = 23.593340, acc = 0.930000\n",
      "epoch [1429] L = 23.577228, acc = 0.930000\n",
      "epoch [1430] L = 23.561145, acc = 0.930000\n",
      "epoch [1431] L = 23.545090, acc = 0.930000\n",
      "epoch [1432] L = 23.529063, acc = 0.930000\n",
      "epoch [1433] L = 23.513064, acc = 0.930000\n",
      "epoch [1434] L = 23.497094, acc = 0.930000\n",
      "epoch [1435] L = 23.481152, acc = 0.930000\n",
      "epoch [1436] L = 23.465237, acc = 0.930000\n",
      "epoch [1437] L = 23.449351, acc = 0.930000\n",
      "epoch [1438] L = 23.433493, acc = 0.930000\n",
      "epoch [1439] L = 23.417663, acc = 0.930000\n",
      "epoch [1440] L = 23.401861, acc = 0.930000\n",
      "epoch [1441] L = 23.386086, acc = 0.930000\n",
      "epoch [1442] L = 23.370339, acc = 0.930000\n",
      "epoch [1443] L = 23.354621, acc = 0.930000\n",
      "epoch [1444] L = 23.338929, acc = 0.930000\n",
      "epoch [1445] L = 23.323266, acc = 0.930000\n",
      "epoch [1446] L = 23.307630, acc = 0.930000\n",
      "epoch [1447] L = 23.292022, acc = 0.930000\n",
      "epoch [1448] L = 23.276441, acc = 0.930000\n",
      "epoch [1449] L = 23.260887, acc = 0.935000\n",
      "epoch [1450] L = 23.245361, acc = 0.935000\n",
      "epoch [1451] L = 23.229863, acc = 0.935000\n",
      "epoch [1452] L = 23.214392, acc = 0.935000\n",
      "epoch [1453] L = 23.198948, acc = 0.935000\n",
      "epoch [1454] L = 23.183531, acc = 0.935000\n",
      "epoch [1455] L = 23.168141, acc = 0.935000\n",
      "epoch [1456] L = 23.152779, acc = 0.935000\n",
      "epoch [1457] L = 23.137444, acc = 0.935000\n",
      "epoch [1458] L = 23.122135, acc = 0.935000\n",
      "epoch [1459] L = 23.106854, acc = 0.935000\n",
      "epoch [1460] L = 23.091600, acc = 0.935000\n",
      "epoch [1461] L = 23.076372, acc = 0.935000\n",
      "epoch [1462] L = 23.061172, acc = 0.935000\n",
      "epoch [1463] L = 23.045998, acc = 0.935000\n",
      "epoch [1464] L = 23.030851, acc = 0.935000\n",
      "epoch [1465] L = 23.015731, acc = 0.935000\n",
      "epoch [1466] L = 23.000637, acc = 0.935000\n",
      "epoch [1467] L = 22.985570, acc = 0.935000\n",
      "epoch [1468] L = 22.970530, acc = 0.935000\n",
      "epoch [1469] L = 22.955516, acc = 0.935000\n",
      "epoch [1470] L = 22.940528, acc = 0.935000\n",
      "epoch [1471] L = 22.925567, acc = 0.935000\n",
      "epoch [1472] L = 22.910633, acc = 0.935000\n",
      "epoch [1473] L = 22.895724, acc = 0.935000\n",
      "epoch [1474] L = 22.880842, acc = 0.935000\n",
      "epoch [1475] L = 22.865986, acc = 0.935000\n",
      "epoch [1476] L = 22.851157, acc = 0.935000\n",
      "epoch [1477] L = 22.836353, acc = 0.935000\n",
      "epoch [1478] L = 22.821576, acc = 0.935000\n",
      "epoch [1479] L = 22.806824, acc = 0.940000\n",
      "epoch [1480] L = 22.792099, acc = 0.940000\n",
      "epoch [1481] L = 22.777400, acc = 0.940000\n",
      "epoch [1482] L = 22.762726, acc = 0.940000\n",
      "epoch [1483] L = 22.748079, acc = 0.940000\n",
      "epoch [1484] L = 22.733457, acc = 0.940000\n",
      "epoch [1485] L = 22.718861, acc = 0.940000\n",
      "epoch [1486] L = 22.704290, acc = 0.940000\n",
      "epoch [1487] L = 22.689746, acc = 0.940000\n",
      "epoch [1488] L = 22.675226, acc = 0.940000\n",
      "epoch [1489] L = 22.660733, acc = 0.940000\n",
      "epoch [1490] L = 22.646265, acc = 0.940000\n",
      "epoch [1491] L = 22.631822, acc = 0.940000\n",
      "epoch [1492] L = 22.617405, acc = 0.940000\n",
      "epoch [1493] L = 22.603014, acc = 0.940000\n",
      "epoch [1494] L = 22.588647, acc = 0.940000\n",
      "epoch [1495] L = 22.574306, acc = 0.940000\n",
      "epoch [1496] L = 22.559990, acc = 0.940000\n",
      "epoch [1497] L = 22.545700, acc = 0.940000\n",
      "epoch [1498] L = 22.531434, acc = 0.940000\n",
      "epoch [1499] L = 22.517194, acc = 0.940000\n",
      "epoch [1500] L = 22.502978, acc = 0.940000\n",
      "epoch [1501] L = 22.488788, acc = 0.940000\n",
      "epoch [1502] L = 22.474623, acc = 0.940000\n",
      "epoch [1503] L = 22.460482, acc = 0.940000\n",
      "epoch [1504] L = 22.446367, acc = 0.940000\n",
      "epoch [1505] L = 22.432276, acc = 0.940000\n",
      "epoch [1506] L = 22.418210, acc = 0.940000\n",
      "epoch [1507] L = 22.404168, acc = 0.940000\n",
      "epoch [1508] L = 22.390152, acc = 0.940000\n",
      "epoch [1509] L = 22.376160, acc = 0.940000\n",
      "epoch [1510] L = 22.362192, acc = 0.940000\n",
      "epoch [1511] L = 22.348249, acc = 0.940000\n",
      "epoch [1512] L = 22.334331, acc = 0.940000\n",
      "epoch [1513] L = 22.320437, acc = 0.940000\n",
      "epoch [1514] L = 22.306567, acc = 0.940000\n",
      "epoch [1515] L = 22.292722, acc = 0.940000\n",
      "epoch [1516] L = 22.278901, acc = 0.940000\n",
      "epoch [1517] L = 22.265105, acc = 0.940000\n",
      "epoch [1518] L = 22.251332, acc = 0.940000\n",
      "epoch [1519] L = 22.237584, acc = 0.940000\n",
      "epoch [1520] L = 22.223860, acc = 0.940000\n",
      "epoch [1521] L = 22.210160, acc = 0.940000\n",
      "epoch [1522] L = 22.196483, acc = 0.940000\n",
      "epoch [1523] L = 22.182831, acc = 0.940000\n",
      "epoch [1524] L = 22.169203, acc = 0.940000\n",
      "epoch [1525] L = 22.155599, acc = 0.940000\n",
      "epoch [1526] L = 22.142018, acc = 0.940000\n",
      "epoch [1527] L = 22.128462, acc = 0.940000\n",
      "epoch [1528] L = 22.114929, acc = 0.940000\n",
      "epoch [1529] L = 22.101420, acc = 0.940000\n",
      "epoch [1530] L = 22.087934, acc = 0.940000\n",
      "epoch [1531] L = 22.074472, acc = 0.940000\n",
      "epoch [1532] L = 22.061034, acc = 0.940000\n",
      "epoch [1533] L = 22.047619, acc = 0.940000\n",
      "epoch [1534] L = 22.034227, acc = 0.940000\n",
      "epoch [1535] L = 22.020859, acc = 0.940000\n",
      "epoch [1536] L = 22.007514, acc = 0.940000\n",
      "epoch [1537] L = 21.994193, acc = 0.940000\n",
      "epoch [1538] L = 21.980895, acc = 0.940000\n",
      "epoch [1539] L = 21.967620, acc = 0.940000\n",
      "epoch [1540] L = 21.954369, acc = 0.940000\n",
      "epoch [1541] L = 21.941140, acc = 0.940000\n",
      "epoch [1542] L = 21.927935, acc = 0.940000\n",
      "epoch [1543] L = 21.914753, acc = 0.940000\n",
      "epoch [1544] L = 21.901593, acc = 0.940000\n",
      "epoch [1545] L = 21.888457, acc = 0.940000\n",
      "epoch [1546] L = 21.875344, acc = 0.940000\n",
      "epoch [1547] L = 21.862253, acc = 0.940000\n",
      "epoch [1548] L = 21.849185, acc = 0.940000\n",
      "epoch [1549] L = 21.836140, acc = 0.940000\n",
      "epoch [1550] L = 21.823118, acc = 0.940000\n",
      "epoch [1551] L = 21.810119, acc = 0.940000\n",
      "epoch [1552] L = 21.797142, acc = 0.940000\n",
      "epoch [1553] L = 21.784187, acc = 0.940000\n",
      "epoch [1554] L = 21.771256, acc = 0.940000\n",
      "epoch [1555] L = 21.758347, acc = 0.940000\n",
      "epoch [1556] L = 21.745460, acc = 0.940000\n",
      "epoch [1557] L = 21.732595, acc = 0.940000\n",
      "epoch [1558] L = 21.719754, acc = 0.940000\n",
      "epoch [1559] L = 21.706934, acc = 0.940000\n",
      "epoch [1560] L = 21.694137, acc = 0.940000\n",
      "epoch [1561] L = 21.681361, acc = 0.940000\n",
      "epoch [1562] L = 21.668609, acc = 0.940000\n",
      "epoch [1563] L = 21.655878, acc = 0.940000\n",
      "epoch [1564] L = 21.643169, acc = 0.940000\n",
      "epoch [1565] L = 21.630483, acc = 0.940000\n",
      "epoch [1566] L = 21.617818, acc = 0.940000\n",
      "epoch [1567] L = 21.605175, acc = 0.940000\n",
      "epoch [1568] L = 21.592555, acc = 0.940000\n",
      "epoch [1569] L = 21.579956, acc = 0.940000\n",
      "epoch [1570] L = 21.567379, acc = 0.940000\n",
      "epoch [1571] L = 21.554824, acc = 0.940000\n",
      "epoch [1572] L = 21.542290, acc = 0.940000\n",
      "epoch [1573] L = 21.529779, acc = 0.940000\n",
      "epoch [1574] L = 21.517289, acc = 0.940000\n",
      "epoch [1575] L = 21.504820, acc = 0.940000\n",
      "epoch [1576] L = 21.492373, acc = 0.940000\n",
      "epoch [1577] L = 21.479948, acc = 0.940000\n",
      "epoch [1578] L = 21.467544, acc = 0.940000\n",
      "epoch [1579] L = 21.455162, acc = 0.940000\n",
      "epoch [1580] L = 21.442801, acc = 0.940000\n",
      "epoch [1581] L = 21.430461, acc = 0.940000\n",
      "epoch [1582] L = 21.418143, acc = 0.940000\n",
      "epoch [1583] L = 21.405846, acc = 0.940000\n",
      "epoch [1584] L = 21.393570, acc = 0.940000\n",
      "epoch [1585] L = 21.381315, acc = 0.940000\n",
      "epoch [1586] L = 21.369082, acc = 0.940000\n",
      "epoch [1587] L = 21.356869, acc = 0.940000\n",
      "epoch [1588] L = 21.344678, acc = 0.940000\n",
      "epoch [1589] L = 21.332507, acc = 0.940000\n",
      "epoch [1590] L = 21.320358, acc = 0.940000\n",
      "epoch [1591] L = 21.308229, acc = 0.940000\n",
      "epoch [1592] L = 21.296122, acc = 0.940000\n",
      "epoch [1593] L = 21.284035, acc = 0.940000\n",
      "epoch [1594] L = 21.271969, acc = 0.940000\n",
      "epoch [1595] L = 21.259923, acc = 0.940000\n",
      "epoch [1596] L = 21.247899, acc = 0.940000\n",
      "epoch [1597] L = 21.235895, acc = 0.940000\n",
      "epoch [1598] L = 21.223912, acc = 0.940000\n",
      "epoch [1599] L = 21.211949, acc = 0.940000\n",
      "epoch [1600] L = 21.200006, acc = 0.940000\n",
      "epoch [1601] L = 21.188085, acc = 0.940000\n",
      "epoch [1602] L = 21.176183, acc = 0.940000\n",
      "epoch [1603] L = 21.164302, acc = 0.940000\n",
      "epoch [1604] L = 21.152442, acc = 0.940000\n",
      "epoch [1605] L = 21.140602, acc = 0.940000\n",
      "epoch [1606] L = 21.128782, acc = 0.940000\n",
      "epoch [1607] L = 21.116982, acc = 0.940000\n",
      "epoch [1608] L = 21.105202, acc = 0.940000\n",
      "epoch [1609] L = 21.093443, acc = 0.940000\n",
      "epoch [1610] L = 21.081704, acc = 0.940000\n",
      "epoch [1611] L = 21.069984, acc = 0.940000\n",
      "epoch [1612] L = 21.058285, acc = 0.940000\n",
      "epoch [1613] L = 21.046606, acc = 0.940000\n",
      "epoch [1614] L = 21.034947, acc = 0.940000\n",
      "epoch [1615] L = 21.023307, acc = 0.940000\n",
      "epoch [1616] L = 21.011687, acc = 0.940000\n",
      "epoch [1617] L = 21.000088, acc = 0.940000\n",
      "epoch [1618] L = 20.988508, acc = 0.940000\n",
      "epoch [1619] L = 20.976947, acc = 0.940000\n",
      "epoch [1620] L = 20.965407, acc = 0.940000\n",
      "epoch [1621] L = 20.953886, acc = 0.945000\n",
      "epoch [1622] L = 20.942384, acc = 0.945000\n",
      "epoch [1623] L = 20.930902, acc = 0.945000\n",
      "epoch [1624] L = 20.919440, acc = 0.945000\n",
      "epoch [1625] L = 20.907997, acc = 0.945000\n",
      "epoch [1626] L = 20.896574, acc = 0.945000\n",
      "epoch [1627] L = 20.885170, acc = 0.945000\n",
      "epoch [1628] L = 20.873785, acc = 0.945000\n",
      "epoch [1629] L = 20.862420, acc = 0.950000\n",
      "epoch [1630] L = 20.851074, acc = 0.950000\n",
      "epoch [1631] L = 20.839747, acc = 0.950000\n",
      "epoch [1632] L = 20.828439, acc = 0.950000\n",
      "epoch [1633] L = 20.817151, acc = 0.950000\n",
      "epoch [1634] L = 20.805881, acc = 0.950000\n",
      "epoch [1635] L = 20.794631, acc = 0.950000\n",
      "epoch [1636] L = 20.783399, acc = 0.950000\n",
      "epoch [1637] L = 20.772187, acc = 0.950000\n",
      "epoch [1638] L = 20.760994, acc = 0.950000\n",
      "epoch [1639] L = 20.749819, acc = 0.950000\n",
      "epoch [1640] L = 20.738663, acc = 0.950000\n",
      "epoch [1641] L = 20.727526, acc = 0.950000\n",
      "epoch [1642] L = 20.716408, acc = 0.950000\n",
      "epoch [1643] L = 20.705309, acc = 0.950000\n",
      "epoch [1644] L = 20.694228, acc = 0.950000\n",
      "epoch [1645] L = 20.683166, acc = 0.950000\n",
      "epoch [1646] L = 20.672123, acc = 0.950000\n",
      "epoch [1647] L = 20.661098, acc = 0.950000\n",
      "epoch [1648] L = 20.650092, acc = 0.950000\n",
      "epoch [1649] L = 20.639104, acc = 0.950000\n",
      "epoch [1650] L = 20.628135, acc = 0.950000\n",
      "epoch [1651] L = 20.617184, acc = 0.950000\n",
      "epoch [1652] L = 20.606251, acc = 0.950000\n",
      "epoch [1653] L = 20.595337, acc = 0.950000\n",
      "epoch [1654] L = 20.584441, acc = 0.950000\n",
      "epoch [1655] L = 20.573563, acc = 0.950000\n",
      "epoch [1656] L = 20.562704, acc = 0.950000\n",
      "epoch [1657] L = 20.551863, acc = 0.950000\n",
      "epoch [1658] L = 20.541039, acc = 0.950000\n",
      "epoch [1659] L = 20.530234, acc = 0.950000\n",
      "epoch [1660] L = 20.519447, acc = 0.950000\n",
      "epoch [1661] L = 20.508678, acc = 0.950000\n",
      "epoch [1662] L = 20.497927, acc = 0.950000\n",
      "epoch [1663] L = 20.487194, acc = 0.950000\n",
      "epoch [1664] L = 20.476479, acc = 0.950000\n",
      "epoch [1665] L = 20.465782, acc = 0.950000\n",
      "epoch [1666] L = 20.455102, acc = 0.950000\n",
      "epoch [1667] L = 20.444441, acc = 0.950000\n",
      "epoch [1668] L = 20.433797, acc = 0.950000\n",
      "epoch [1669] L = 20.423171, acc = 0.950000\n",
      "epoch [1670] L = 20.412562, acc = 0.950000\n",
      "epoch [1671] L = 20.401971, acc = 0.950000\n",
      "epoch [1672] L = 20.391398, acc = 0.950000\n",
      "epoch [1673] L = 20.380842, acc = 0.950000\n",
      "epoch [1674] L = 20.370304, acc = 0.950000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch [1675] L = 20.359783, acc = 0.950000\n",
      "epoch [1676] L = 20.349279, acc = 0.950000\n",
      "epoch [1677] L = 20.338793, acc = 0.950000\n",
      "epoch [1678] L = 20.328325, acc = 0.950000\n",
      "epoch [1679] L = 20.317874, acc = 0.950000\n",
      "epoch [1680] L = 20.307440, acc = 0.950000\n",
      "epoch [1681] L = 20.297023, acc = 0.950000\n",
      "epoch [1682] L = 20.286623, acc = 0.950000\n",
      "epoch [1683] L = 20.276241, acc = 0.950000\n",
      "epoch [1684] L = 20.265876, acc = 0.950000\n",
      "epoch [1685] L = 20.255527, acc = 0.950000\n",
      "epoch [1686] L = 20.245196, acc = 0.950000\n",
      "epoch [1687] L = 20.234882, acc = 0.950000\n",
      "epoch [1688] L = 20.224585, acc = 0.950000\n",
      "epoch [1689] L = 20.214305, acc = 0.950000\n",
      "epoch [1690] L = 20.204042, acc = 0.950000\n",
      "epoch [1691] L = 20.193795, acc = 0.950000\n",
      "epoch [1692] L = 20.183566, acc = 0.950000\n",
      "epoch [1693] L = 20.173353, acc = 0.950000\n",
      "epoch [1694] L = 20.163157, acc = 0.950000\n",
      "epoch [1695] L = 20.152978, acc = 0.950000\n",
      "epoch [1696] L = 20.142815, acc = 0.950000\n",
      "epoch [1697] L = 20.132669, acc = 0.950000\n",
      "epoch [1698] L = 20.122540, acc = 0.950000\n",
      "epoch [1699] L = 20.112427, acc = 0.950000\n",
      "epoch [1700] L = 20.102330, acc = 0.950000\n",
      "epoch [1701] L = 20.092251, acc = 0.950000\n",
      "epoch [1702] L = 20.082187, acc = 0.950000\n",
      "epoch [1703] L = 20.072140, acc = 0.950000\n",
      "epoch [1704] L = 20.062110, acc = 0.950000\n",
      "epoch [1705] L = 20.052096, acc = 0.950000\n",
      "epoch [1706] L = 20.042098, acc = 0.950000\n",
      "epoch [1707] L = 20.032116, acc = 0.950000\n",
      "epoch [1708] L = 20.022151, acc = 0.950000\n",
      "epoch [1709] L = 20.012202, acc = 0.950000\n",
      "epoch [1710] L = 20.002269, acc = 0.950000\n",
      "epoch [1711] L = 19.992352, acc = 0.950000\n",
      "epoch [1712] L = 19.982451, acc = 0.950000\n",
      "epoch [1713] L = 19.972567, acc = 0.950000\n",
      "epoch [1714] L = 19.962698, acc = 0.950000\n",
      "epoch [1715] L = 19.952845, acc = 0.950000\n",
      "epoch [1716] L = 19.943009, acc = 0.950000\n",
      "epoch [1717] L = 19.933188, acc = 0.950000\n",
      "epoch [1718] L = 19.923383, acc = 0.950000\n",
      "epoch [1719] L = 19.913594, acc = 0.950000\n",
      "epoch [1720] L = 19.903821, acc = 0.950000\n",
      "epoch [1721] L = 19.894063, acc = 0.950000\n",
      "epoch [1722] L = 19.884322, acc = 0.950000\n",
      "epoch [1723] L = 19.874595, acc = 0.950000\n",
      "epoch [1724] L = 19.864885, acc = 0.950000\n",
      "epoch [1725] L = 19.855190, acc = 0.950000\n",
      "epoch [1726] L = 19.845511, acc = 0.950000\n",
      "epoch [1727] L = 19.835848, acc = 0.950000\n",
      "epoch [1728] L = 19.826200, acc = 0.950000\n",
      "epoch [1729] L = 19.816567, acc = 0.950000\n",
      "epoch [1730] L = 19.806950, acc = 0.950000\n",
      "epoch [1731] L = 19.797348, acc = 0.950000\n",
      "epoch [1732] L = 19.787762, acc = 0.950000\n",
      "epoch [1733] L = 19.778191, acc = 0.950000\n",
      "epoch [1734] L = 19.768635, acc = 0.950000\n",
      "epoch [1735] L = 19.759095, acc = 0.950000\n",
      "epoch [1736] L = 19.749570, acc = 0.950000\n",
      "epoch [1737] L = 19.740060, acc = 0.950000\n",
      "epoch [1738] L = 19.730565, acc = 0.950000\n",
      "epoch [1739] L = 19.721086, acc = 0.950000\n",
      "epoch [1740] L = 19.711621, acc = 0.950000\n",
      "epoch [1741] L = 19.702172, acc = 0.950000\n",
      "epoch [1742] L = 19.692738, acc = 0.950000\n",
      "epoch [1743] L = 19.683318, acc = 0.950000\n",
      "epoch [1744] L = 19.673914, acc = 0.950000\n",
      "epoch [1745] L = 19.664524, acc = 0.950000\n",
      "epoch [1746] L = 19.655150, acc = 0.950000\n",
      "epoch [1747] L = 19.645790, acc = 0.950000\n",
      "epoch [1748] L = 19.636445, acc = 0.950000\n",
      "epoch [1749] L = 19.627115, acc = 0.950000\n",
      "epoch [1750] L = 19.617800, acc = 0.950000\n",
      "epoch [1751] L = 19.608500, acc = 0.950000\n",
      "epoch [1752] L = 19.599214, acc = 0.950000\n",
      "epoch [1753] L = 19.589943, acc = 0.950000\n",
      "epoch [1754] L = 19.580686, acc = 0.950000\n",
      "epoch [1755] L = 19.571445, acc = 0.950000\n",
      "epoch [1756] L = 19.562217, acc = 0.950000\n",
      "epoch [1757] L = 19.553004, acc = 0.950000\n",
      "epoch [1758] L = 19.543806, acc = 0.950000\n",
      "epoch [1759] L = 19.534622, acc = 0.950000\n",
      "epoch [1760] L = 19.525453, acc = 0.950000\n",
      "epoch [1761] L = 19.516298, acc = 0.950000\n",
      "epoch [1762] L = 19.507158, acc = 0.950000\n",
      "epoch [1763] L = 19.498031, acc = 0.950000\n",
      "epoch [1764] L = 19.488919, acc = 0.950000\n",
      "epoch [1765] L = 19.479822, acc = 0.950000\n",
      "epoch [1766] L = 19.470738, acc = 0.950000\n",
      "epoch [1767] L = 19.461669, acc = 0.950000\n",
      "epoch [1768] L = 19.452614, acc = 0.950000\n",
      "epoch [1769] L = 19.443573, acc = 0.950000\n",
      "epoch [1770] L = 19.434546, acc = 0.950000\n",
      "epoch [1771] L = 19.425534, acc = 0.950000\n",
      "epoch [1772] L = 19.416535, acc = 0.950000\n",
      "epoch [1773] L = 19.407550, acc = 0.950000\n",
      "epoch [1774] L = 19.398580, acc = 0.950000\n",
      "epoch [1775] L = 19.389623, acc = 0.950000\n",
      "epoch [1776] L = 19.380680, acc = 0.950000\n",
      "epoch [1777] L = 19.371751, acc = 0.950000\n",
      "epoch [1778] L = 19.362836, acc = 0.950000\n",
      "epoch [1779] L = 19.353935, acc = 0.950000\n",
      "epoch [1780] L = 19.345048, acc = 0.950000\n",
      "epoch [1781] L = 19.336174, acc = 0.950000\n",
      "epoch [1782] L = 19.327314, acc = 0.950000\n",
      "epoch [1783] L = 19.318468, acc = 0.950000\n",
      "epoch [1784] L = 19.309635, acc = 0.950000\n",
      "epoch [1785] L = 19.300816, acc = 0.950000\n",
      "epoch [1786] L = 19.292011, acc = 0.950000\n",
      "epoch [1787] L = 19.283219, acc = 0.950000\n",
      "epoch [1788] L = 19.274441, acc = 0.950000\n",
      "epoch [1789] L = 19.265676, acc = 0.950000\n",
      "epoch [1790] L = 19.256925, acc = 0.950000\n",
      "epoch [1791] L = 19.248187, acc = 0.950000\n",
      "epoch [1792] L = 19.239463, acc = 0.950000\n",
      "epoch [1793] L = 19.230752, acc = 0.950000\n",
      "epoch [1794] L = 19.222054, acc = 0.950000\n",
      "epoch [1795] L = 19.213370, acc = 0.950000\n",
      "epoch [1796] L = 19.204699, acc = 0.950000\n",
      "epoch [1797] L = 19.196041, acc = 0.950000\n",
      "epoch [1798] L = 19.187396, acc = 0.950000\n",
      "epoch [1799] L = 19.178765, acc = 0.950000\n",
      "epoch [1800] L = 19.170147, acc = 0.950000\n",
      "epoch [1801] L = 19.161542, acc = 0.950000\n",
      "epoch [1802] L = 19.152950, acc = 0.950000\n",
      "epoch [1803] L = 19.144371, acc = 0.950000\n",
      "epoch [1804] L = 19.135805, acc = 0.950000\n",
      "epoch [1805] L = 19.127252, acc = 0.950000\n",
      "epoch [1806] L = 19.118712, acc = 0.950000\n",
      "epoch [1807] L = 19.110186, acc = 0.950000\n",
      "epoch [1808] L = 19.101672, acc = 0.950000\n",
      "epoch [1809] L = 19.093171, acc = 0.950000\n",
      "epoch [1810] L = 19.084682, acc = 0.950000\n",
      "epoch [1811] L = 19.076207, acc = 0.950000\n",
      "epoch [1812] L = 19.067745, acc = 0.950000\n",
      "epoch [1813] L = 19.059295, acc = 0.950000\n",
      "epoch [1814] L = 19.050858, acc = 0.950000\n",
      "epoch [1815] L = 19.042434, acc = 0.950000\n",
      "epoch [1816] L = 19.034022, acc = 0.950000\n",
      "epoch [1817] L = 19.025623, acc = 0.950000\n",
      "epoch [1818] L = 19.017237, acc = 0.950000\n",
      "epoch [1819] L = 19.008863, acc = 0.950000\n",
      "epoch [1820] L = 19.000502, acc = 0.950000\n",
      "epoch [1821] L = 18.992153, acc = 0.950000\n",
      "epoch [1822] L = 18.983817, acc = 0.950000\n",
      "epoch [1823] L = 18.975494, acc = 0.950000\n",
      "epoch [1824] L = 18.967183, acc = 0.950000\n",
      "epoch [1825] L = 18.958884, acc = 0.950000\n",
      "epoch [1826] L = 18.950598, acc = 0.950000\n",
      "epoch [1827] L = 18.942324, acc = 0.950000\n",
      "epoch [1828] L = 18.934062, acc = 0.950000\n",
      "epoch [1829] L = 18.925813, acc = 0.950000\n",
      "epoch [1830] L = 18.917576, acc = 0.950000\n",
      "epoch [1831] L = 18.909351, acc = 0.950000\n",
      "epoch [1832] L = 18.901139, acc = 0.950000\n",
      "epoch [1833] L = 18.892938, acc = 0.950000\n",
      "epoch [1834] L = 18.884750, acc = 0.950000\n",
      "epoch [1835] L = 18.876574, acc = 0.950000\n",
      "epoch [1836] L = 18.868410, acc = 0.950000\n",
      "epoch [1837] L = 18.860258, acc = 0.950000\n",
      "epoch [1838] L = 18.852119, acc = 0.950000\n",
      "epoch [1839] L = 18.843991, acc = 0.950000\n",
      "epoch [1840] L = 18.835875, acc = 0.950000\n",
      "epoch [1841] L = 18.827771, acc = 0.950000\n",
      "epoch [1842] L = 18.819680, acc = 0.950000\n",
      "epoch [1843] L = 18.811600, acc = 0.950000\n",
      "epoch [1844] L = 18.803532, acc = 0.950000\n",
      "epoch [1845] L = 18.795476, acc = 0.950000\n",
      "epoch [1846] L = 18.787431, acc = 0.950000\n",
      "epoch [1847] L = 18.779399, acc = 0.950000\n",
      "epoch [1848] L = 18.771378, acc = 0.950000\n",
      "epoch [1849] L = 18.763369, acc = 0.950000\n",
      "epoch [1850] L = 18.755372, acc = 0.950000\n",
      "epoch [1851] L = 18.747386, acc = 0.950000\n",
      "epoch [1852] L = 18.739412, acc = 0.950000\n",
      "epoch [1853] L = 18.731450, acc = 0.950000\n",
      "epoch [1854] L = 18.723499, acc = 0.950000\n",
      "epoch [1855] L = 18.715560, acc = 0.950000\n",
      "epoch [1856] L = 18.707633, acc = 0.950000\n",
      "epoch [1857] L = 18.699717, acc = 0.950000\n",
      "epoch [1858] L = 18.691812, acc = 0.950000\n",
      "epoch [1859] L = 18.683919, acc = 0.950000\n",
      "epoch [1860] L = 18.676038, acc = 0.950000\n",
      "epoch [1861] L = 18.668168, acc = 0.950000\n",
      "epoch [1862] L = 18.660309, acc = 0.950000\n",
      "epoch [1863] L = 18.652462, acc = 0.950000\n",
      "epoch [1864] L = 18.644626, acc = 0.950000\n",
      "epoch [1865] L = 18.636801, acc = 0.950000\n",
      "epoch [1866] L = 18.628988, acc = 0.950000\n",
      "epoch [1867] L = 18.621185, acc = 0.950000\n",
      "epoch [1868] L = 18.613395, acc = 0.950000\n",
      "epoch [1869] L = 18.605615, acc = 0.950000\n",
      "epoch [1870] L = 18.597846, acc = 0.950000\n",
      "epoch [1871] L = 18.590089, acc = 0.950000\n",
      "epoch [1872] L = 18.582343, acc = 0.950000\n",
      "epoch [1873] L = 18.574608, acc = 0.950000\n",
      "epoch [1874] L = 18.566884, acc = 0.950000\n",
      "epoch [1875] L = 18.559171, acc = 0.950000\n",
      "epoch [1876] L = 18.551469, acc = 0.950000\n",
      "epoch [1877] L = 18.543778, acc = 0.950000\n",
      "epoch [1878] L = 18.536098, acc = 0.950000\n",
      "epoch [1879] L = 18.528429, acc = 0.950000\n",
      "epoch [1880] L = 18.520771, acc = 0.950000\n",
      "epoch [1881] L = 18.513124, acc = 0.950000\n",
      "epoch [1882] L = 18.505487, acc = 0.950000\n",
      "epoch [1883] L = 18.497862, acc = 0.950000\n",
      "epoch [1884] L = 18.490247, acc = 0.950000\n",
      "epoch [1885] L = 18.482644, acc = 0.950000\n",
      "epoch [1886] L = 18.475051, acc = 0.950000\n",
      "epoch [1887] L = 18.467468, acc = 0.950000\n",
      "epoch [1888] L = 18.459897, acc = 0.950000\n",
      "epoch [1889] L = 18.452336, acc = 0.950000\n",
      "epoch [1890] L = 18.444786, acc = 0.950000\n",
      "epoch [1891] L = 18.437246, acc = 0.950000\n",
      "epoch [1892] L = 18.429717, acc = 0.950000\n",
      "epoch [1893] L = 18.422199, acc = 0.950000\n",
      "epoch [1894] L = 18.414691, acc = 0.950000\n",
      "epoch [1895] L = 18.407194, acc = 0.950000\n",
      "epoch [1896] L = 18.399707, acc = 0.950000\n",
      "epoch [1897] L = 18.392231, acc = 0.950000\n",
      "epoch [1898] L = 18.384765, acc = 0.950000\n",
      "epoch [1899] L = 18.377310, acc = 0.950000\n",
      "epoch [1900] L = 18.369865, acc = 0.950000\n",
      "epoch [1901] L = 18.362431, acc = 0.950000\n",
      "epoch [1902] L = 18.355006, acc = 0.950000\n",
      "epoch [1903] L = 18.347593, acc = 0.950000\n",
      "epoch [1904] L = 18.340189, acc = 0.950000\n",
      "epoch [1905] L = 18.332796, acc = 0.950000\n",
      "epoch [1906] L = 18.325413, acc = 0.950000\n",
      "epoch [1907] L = 18.318041, acc = 0.950000\n",
      "epoch [1908] L = 18.310679, acc = 0.950000\n",
      "epoch [1909] L = 18.303326, acc = 0.950000\n",
      "epoch [1910] L = 18.295984, acc = 0.950000\n",
      "epoch [1911] L = 18.288653, acc = 0.950000\n",
      "epoch [1912] L = 18.281331, acc = 0.950000\n",
      "epoch [1913] L = 18.274019, acc = 0.950000\n",
      "epoch [1914] L = 18.266718, acc = 0.950000\n",
      "epoch [1915] L = 18.259427, acc = 0.950000\n",
      "epoch [1916] L = 18.252145, acc = 0.950000\n",
      "epoch [1917] L = 18.244874, acc = 0.950000\n",
      "epoch [1918] L = 18.237612, acc = 0.950000\n",
      "epoch [1919] L = 18.230361, acc = 0.950000\n",
      "epoch [1920] L = 18.223120, acc = 0.950000\n",
      "epoch [1921] L = 18.215888, acc = 0.950000\n",
      "epoch [1922] L = 18.208666, acc = 0.950000\n",
      "epoch [1923] L = 18.201455, acc = 0.950000\n",
      "epoch [1924] L = 18.194253, acc = 0.950000\n",
      "epoch [1925] L = 18.187061, acc = 0.950000\n",
      "epoch [1926] L = 18.179878, acc = 0.950000\n",
      "epoch [1927] L = 18.172706, acc = 0.950000\n",
      "epoch [1928] L = 18.165543, acc = 0.950000\n",
      "epoch [1929] L = 18.158390, acc = 0.950000\n",
      "epoch [1930] L = 18.151247, acc = 0.950000\n",
      "epoch [1931] L = 18.144113, acc = 0.950000\n",
      "epoch [1932] L = 18.136989, acc = 0.950000\n",
      "epoch [1933] L = 18.129875, acc = 0.950000\n",
      "epoch [1934] L = 18.122770, acc = 0.950000\n",
      "epoch [1935] L = 18.115675, acc = 0.950000\n",
      "epoch [1936] L = 18.108590, acc = 0.950000\n",
      "epoch [1937] L = 18.101514, acc = 0.950000\n",
      "epoch [1938] L = 18.094447, acc = 0.950000\n",
      "epoch [1939] L = 18.087390, acc = 0.950000\n",
      "epoch [1940] L = 18.080343, acc = 0.950000\n",
      "epoch [1941] L = 18.073305, acc = 0.950000\n",
      "epoch [1942] L = 18.066276, acc = 0.950000\n",
      "epoch [1943] L = 18.059257, acc = 0.950000\n",
      "epoch [1944] L = 18.052248, acc = 0.950000\n",
      "epoch [1945] L = 18.045247, acc = 0.950000\n",
      "epoch [1946] L = 18.038256, acc = 0.955000\n",
      "epoch [1947] L = 18.031275, acc = 0.955000\n",
      "epoch [1948] L = 18.024302, acc = 0.955000\n",
      "epoch [1949] L = 18.017339, acc = 0.955000\n",
      "epoch [1950] L = 18.010385, acc = 0.955000\n",
      "epoch [1951] L = 18.003441, acc = 0.955000\n",
      "epoch [1952] L = 17.996505, acc = 0.955000\n",
      "epoch [1953] L = 17.989579, acc = 0.955000\n",
      "epoch [1954] L = 17.982662, acc = 0.955000\n",
      "epoch [1955] L = 17.975755, acc = 0.955000\n",
      "epoch [1956] L = 17.968856, acc = 0.955000\n",
      "epoch [1957] L = 17.961966, acc = 0.955000\n",
      "epoch [1958] L = 17.955086, acc = 0.955000\n",
      "epoch [1959] L = 17.948214, acc = 0.955000\n",
      "epoch [1960] L = 17.941352, acc = 0.955000\n",
      "epoch [1961] L = 17.934499, acc = 0.955000\n",
      "epoch [1962] L = 17.927654, acc = 0.955000\n",
      "epoch [1963] L = 17.920819, acc = 0.955000\n",
      "epoch [1964] L = 17.913993, acc = 0.955000\n",
      "epoch [1965] L = 17.907175, acc = 0.955000\n",
      "epoch [1966] L = 17.900367, acc = 0.955000\n",
      "epoch [1967] L = 17.893567, acc = 0.955000\n",
      "epoch [1968] L = 17.886776, acc = 0.955000\n",
      "epoch [1969] L = 17.879994, acc = 0.955000\n",
      "epoch [1970] L = 17.873221, acc = 0.955000\n",
      "epoch [1971] L = 17.866457, acc = 0.955000\n",
      "epoch [1972] L = 17.859701, acc = 0.955000\n",
      "epoch [1973] L = 17.852955, acc = 0.955000\n",
      "epoch [1974] L = 17.846217, acc = 0.955000\n",
      "epoch [1975] L = 17.839488, acc = 0.955000\n",
      "epoch [1976] L = 17.832767, acc = 0.955000\n",
      "epoch [1977] L = 17.826055, acc = 0.955000\n",
      "epoch [1978] L = 17.819352, acc = 0.955000\n",
      "epoch [1979] L = 17.812658, acc = 0.955000\n",
      "epoch [1980] L = 17.805972, acc = 0.955000\n",
      "epoch [1981] L = 17.799295, acc = 0.955000\n",
      "epoch [1982] L = 17.792626, acc = 0.955000\n",
      "epoch [1983] L = 17.785966, acc = 0.955000\n",
      "epoch [1984] L = 17.779314, acc = 0.955000\n",
      "epoch [1985] L = 17.772671, acc = 0.955000\n",
      "epoch [1986] L = 17.766037, acc = 0.955000\n",
      "epoch [1987] L = 17.759411, acc = 0.955000\n",
      "epoch [1988] L = 17.752793, acc = 0.955000\n",
      "epoch [1989] L = 17.746184, acc = 0.955000\n",
      "epoch [1990] L = 17.739583, acc = 0.955000\n",
      "epoch [1991] L = 17.732991, acc = 0.955000\n",
      "epoch [1992] L = 17.726407, acc = 0.955000\n",
      "epoch [1993] L = 17.719832, acc = 0.955000\n",
      "epoch [1994] L = 17.713264, acc = 0.955000\n",
      "epoch [1995] L = 17.706706, acc = 0.955000\n",
      "epoch [1996] L = 17.700155, acc = 0.955000\n",
      "epoch [1997] L = 17.693613, acc = 0.955000\n",
      "epoch [1998] L = 17.687079, acc = 0.955000\n",
      "epoch [1999] L = 17.680553, acc = 0.955000\n"
     ]
    }
   ],
   "source": [
    "# back-propagation\n",
    "def backpropagation(n, x, t):#参数结构体、原数据坐标和标签\n",
    "    for i in range(n.n_epoch):\n",
    "        # forward to calculate each node's output\n",
    "        forward(n, x)\n",
    "        \n",
    "        # print loss, accuracy\n",
    "        #这里就是我们定义的Ed\n",
    "        L = np.sum((n.z2 - t)**2)\n",
    "        \n",
    "        y_pred = np.argmax(nn.z2, axis=1)\n",
    "        #直接用了sklearn评估，自己写对比标签也可以\n",
    "        #acc = np.mean(y_pred == y_true)\n",
    "        acc = accuracy_score(y_true, y_pred)\n",
    "        \n",
    "        print(\"epoch [%4d] L = %f, acc = %f\" % (i, L, acc))\n",
    "        \n",
    "        # calc weights update\n",
    "        d2 = n.z2*(1-n.z2)*(t - n.z2)\n",
    "        d1 = n.z1*(1-n.z1)*(np.dot(d2, n.W2.T))\n",
    "        \n",
    "        # update weights\n",
    "        n.W2 += n.epsilon * np.dot(n.z1.T, d2)\n",
    "        n.b2 += n.epsilon * np.sum(d2, axis=0)\n",
    "        n.W1 += n.epsilon * np.dot(x.T, d1)\n",
    "        n.b1 += n.epsilon * np.sum(d1, axis=0)\n",
    "\n",
    "nn.n_epoch = 2000\n",
    "backpropagation(nn, x, t)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "02fec66a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot data\n",
    "y_pred = np.argmax(nn.z2, axis=1)\n",
    "\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y, cmap=plt.cm.Spectral)\n",
    "plt.title(\"ground truth\")\n",
    "plt.show()\n",
    "\n",
    "plt.scatter(x[:, 0], x[:, 1], c=y_pred, cmap=plt.cm.Spectral)\n",
    "plt.title(\"predicted\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1afa0015",
   "metadata": {},
   "source": [
    "**使用类的方法封装多层神经网络（程序的封装性更好，和前面基本无差）**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ec7e717d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn import datasets, linear_model\n",
    "from sklearn.metrics import accuracy_score\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# define sigmod\n",
    "def sigmod(X):\n",
    "    return 1.0/(1+np.exp(-X))\n",
    "\n",
    "\n",
    "# generate the NN model\n",
    "class NN_Model:\n",
    "    def __init__(self, nodes=None):\n",
    "        self.epsilon = 0.01                 # learning rate\n",
    "        self.n_epoch = 1000                 # iterative number\n",
    "        \n",
    "        if not nodes:\n",
    "            self.nodes = [2, 8, 2]          # default nodes size (from input -> output)\n",
    "        else:\n",
    "            self.nodes = nodes\n",
    "    \n",
    "    def init_weight(self):\n",
    "        W = []\n",
    "        B = []\n",
    "        \n",
    "        n_layer = len(self.nodes)\n",
    "        for i in range(n_layer-1):\n",
    "            w = np.random.randn(self.nodes[i], self.nodes[i+1]) / np.sqrt(self.nodes[i])\n",
    "            b = np.random.randn(1, self.nodes[i+1])\n",
    "            \n",
    "            W.append(w)\n",
    "            B.append(b)\n",
    "            \n",
    "        self.W = W\n",
    "        self.B = B\n",
    "    \n",
    "    def forward(self, X):\n",
    "        Z = []\n",
    "        x0 = X\n",
    "        for i in range(len(self.nodes)-1):\n",
    "            z = sigmod(np.dot(x0, self.W[i]) + self.B[i])\n",
    "            x0 = z\n",
    "            \n",
    "            Z.append(z)\n",
    "        \n",
    "        self.Z = Z\n",
    "        return Z[-1]\n",
    "        \n",
    "    # back-propagation\n",
    "    def backpropagation(self, X, y, n_epoch=None, epsilon=None):\n",
    "        if not n_epoch: n_epoch = self.n_epoch\n",
    "        if not epsilon: epsilon = self.epsilon\n",
    "        \n",
    "        self.X = X\n",
    "        self.Y = y\n",
    "        \n",
    "        for i in range(n_epoch):\n",
    "            # forward to calculate each node's output\n",
    "            self.forward(X)\n",
    "\n",
    "            self.evaluate()\n",
    "            \n",
    "            # calc weights update\n",
    "            W = self.W\n",
    "            B = self.B\n",
    "            Z = self.Z\n",
    "            \n",
    "            D = []\n",
    "            d0 = y\n",
    "            n_layer = len(self.nodes)\n",
    "            for j in range(n_layer-1, 0, -1):\n",
    "                jj = j - 1\n",
    "                z = self.Z[jj]\n",
    "                \n",
    "                if j == n_layer - 1:\n",
    "                    d = z*(1-z)*(d0 - z)\n",
    "                else:\n",
    "                    d = z*(1-z)*np.dot(d0, W[j].T)\n",
    "                    \n",
    "                d0 = d\n",
    "                D.insert(0, d)\n",
    "            \n",
    "            # update weights\n",
    "            for j in range(n_layer-1, 0, -1):\n",
    "                jj = j - 1\n",
    "                \n",
    "                if jj != 0:\n",
    "                    W[jj] += epsilon * np.dot(Z[jj-1].T, D[jj])\n",
    "                else:\n",
    "                    W[jj] += epsilon * np.dot(X.T, D[jj])\n",
    "                    \n",
    "                B[jj] += epsilon * np.sum(D[jj], axis=0)\n",
    "        \n",
    "    def evaluate(self):\n",
    "        z = self.Z[-1]\n",
    "        \n",
    "        # print loss, accuracy\n",
    "        L = np.sum((z - self.Y)**2)\n",
    "            \n",
    "        y_pred = np.argmax(z, axis=1)\n",
    "        y_true = np.argmax(self.Y, axis=1)\n",
    "        acc = accuracy_score(y_true, y_pred)\n",
    "        \n",
    "        print(\"L = %f, acc = %f\" % (L, acc))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "a7ac869b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# generate sample data\n",
    "np.random.seed(0)\n",
    "X, y = datasets.make_moons(200, noise=0.20)\n",
    "\n",
    "# generate nn output target\n",
    "t = np.zeros((X.shape[0], 2))\n",
    "t[np.where(y==0), 0] = 1\n",
    "t[np.where(y==1), 1] = 1\n",
    "\n",
    "# plot data\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Spectral)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2d14b282",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 104.605395, acc = 0.500000\n",
      "L = 102.516986, acc = 0.500000\n",
      "L = 101.351079, acc = 0.500000\n",
      "L = 100.702155, acc = 0.500000\n",
      "L = 100.311377, acc = 0.500000\n",
      "L = 100.042273, acc = 0.500000\n",
      "L = 99.829036, acc = 0.500000\n",
      "L = 99.641080, acc = 0.500000\n",
      "L = 99.464293, acc = 0.500000\n",
      "L = 99.292057, acc = 0.505000\n",
      "L = 99.121118, acc = 0.640000\n",
      "L = 98.949721, acc = 0.725000\n",
      "L = 98.776772, acc = 0.790000\n",
      "L = 98.601463, acc = 0.810000\n",
      "L = 98.423105, acc = 0.820000\n",
      "L = 98.241050, acc = 0.820000\n",
      "L = 98.054652, acc = 0.825000\n",
      "L = 97.863256, acc = 0.830000\n",
      "L = 97.666184, acc = 0.830000\n",
      "L = 97.462728, acc = 0.840000\n",
      "L = 97.252148, acc = 0.840000\n",
      "L = 97.033672, acc = 0.840000\n",
      "L = 96.806486, acc = 0.840000\n",
      "L = 96.569738, acc = 0.840000\n",
      "L = 96.322534, acc = 0.840000\n",
      "L = 96.063939, acc = 0.845000\n",
      "L = 95.792976, acc = 0.840000\n",
      "L = 95.508628, acc = 0.840000\n",
      "L = 95.209839, acc = 0.830000\n",
      "L = 94.895523, acc = 0.835000\n",
      "L = 94.564565, acc = 0.840000\n",
      "L = 94.215831, acc = 0.835000\n",
      "L = 93.848182, acc = 0.840000\n",
      "L = 93.460480, acc = 0.835000\n",
      "L = 93.051610, acc = 0.830000\n",
      "L = 92.620493, acc = 0.830000\n",
      "L = 92.166108, acc = 0.830000\n",
      "L = 91.687511, acc = 0.830000\n",
      "L = 91.183858, acc = 0.830000\n",
      "L = 90.654426, acc = 0.830000\n",
      "L = 90.098631, acc = 0.830000\n",
      "L = 89.516051, acc = 0.825000\n",
      "L = 88.906439, acc = 0.825000\n",
      "L = 88.269733, acc = 0.825000\n",
      "L = 87.606068, acc = 0.830000\n",
      "L = 86.915774, acc = 0.830000\n",
      "L = 86.199377, acc = 0.830000\n",
      "L = 85.457597, acc = 0.830000\n",
      "L = 84.691336, acc = 0.830000\n",
      "L = 83.901671, acc = 0.830000\n",
      "L = 83.089843, acc = 0.830000\n",
      "L = 82.257249, acc = 0.830000\n",
      "L = 81.405424, acc = 0.830000\n",
      "L = 80.536041, acc = 0.830000\n",
      "L = 79.650893, acc = 0.825000\n",
      "L = 78.751887, acc = 0.825000\n",
      "L = 77.841030, acc = 0.825000\n",
      "L = 76.920421, acc = 0.825000\n",
      "L = 75.992235, acc = 0.825000\n",
      "L = 75.058707, acc = 0.825000\n",
      "L = 74.122116, acc = 0.825000\n",
      "L = 73.184762, acc = 0.825000\n",
      "L = 72.248945, acc = 0.825000\n",
      "L = 71.316943, acc = 0.825000\n",
      "L = 70.390986, acc = 0.825000\n",
      "L = 69.473233, acc = 0.825000\n",
      "L = 68.565747, acc = 0.830000\n",
      "L = 67.670476, acc = 0.825000\n",
      "L = 66.789229, acc = 0.825000\n",
      "L = 65.923663, acc = 0.825000\n",
      "L = 65.075270, acc = 0.825000\n",
      "L = 64.245366, acc = 0.825000\n",
      "L = 63.435084, acc = 0.825000\n",
      "L = 62.645374, acc = 0.825000\n",
      "L = 61.877004, acc = 0.825000\n",
      "L = 61.130566, acc = 0.825000\n",
      "L = 60.406478, acc = 0.825000\n",
      "L = 59.705001, acc = 0.825000\n",
      "L = 59.026246, acc = 0.825000\n",
      "L = 58.370186, acc = 0.825000\n",
      "L = 57.736674, acc = 0.825000\n",
      "L = 57.125453, acc = 0.825000\n",
      "L = 56.536172, acc = 0.825000\n",
      "L = 55.968399, acc = 0.825000\n",
      "L = 55.421634, acc = 0.825000\n",
      "L = 54.895323, acc = 0.825000\n",
      "L = 54.388869, acc = 0.825000\n",
      "L = 53.901640, acc = 0.825000\n",
      "L = 53.432983, acc = 0.825000\n",
      "L = 52.982228, acc = 0.825000\n",
      "L = 52.548699, acc = 0.830000\n",
      "L = 52.131718, acc = 0.830000\n",
      "L = 51.730612, acc = 0.830000\n",
      "L = 51.344717, acc = 0.830000\n",
      "L = 50.973382, acc = 0.830000\n",
      "L = 50.615972, acc = 0.830000\n",
      "L = 50.271869, acc = 0.835000\n",
      "L = 49.940478, acc = 0.835000\n",
      "L = 49.621222, acc = 0.835000\n",
      "L = 49.313551, acc = 0.835000\n",
      "L = 49.016934, acc = 0.835000\n",
      "L = 48.730867, acc = 0.840000\n",
      "L = 48.454866, acc = 0.840000\n",
      "L = 48.188472, acc = 0.840000\n",
      "L = 47.931250, acc = 0.840000\n",
      "L = 47.682784, acc = 0.835000\n",
      "L = 47.442682, acc = 0.835000\n",
      "L = 47.210573, acc = 0.835000\n",
      "L = 46.986104, acc = 0.835000\n",
      "L = 46.768942, acc = 0.835000\n",
      "L = 46.558773, acc = 0.835000\n",
      "L = 46.355299, acc = 0.835000\n",
      "L = 46.158241, acc = 0.835000\n",
      "L = 45.967333, acc = 0.835000\n",
      "L = 45.782323, acc = 0.835000\n",
      "L = 45.602977, acc = 0.835000\n",
      "L = 45.429069, acc = 0.835000\n",
      "L = 45.260390, acc = 0.835000\n",
      "L = 45.096738, acc = 0.835000\n",
      "L = 44.937925, acc = 0.830000\n",
      "L = 44.783772, acc = 0.830000\n",
      "L = 44.634109, acc = 0.830000\n",
      "L = 44.488775, acc = 0.830000\n",
      "L = 44.347618, acc = 0.830000\n",
      "L = 44.210492, acc = 0.830000\n",
      "L = 44.077260, acc = 0.830000\n",
      "L = 43.947789, acc = 0.830000\n",
      "L = 43.821956, acc = 0.835000\n",
      "L = 43.699641, acc = 0.835000\n",
      "L = 43.580730, acc = 0.835000\n",
      "L = 43.465114, acc = 0.835000\n",
      "L = 43.352689, acc = 0.835000\n",
      "L = 43.243355, acc = 0.835000\n",
      "L = 43.137016, acc = 0.835000\n",
      "L = 43.033581, acc = 0.835000\n",
      "L = 42.932962, acc = 0.835000\n",
      "L = 42.835072, acc = 0.835000\n",
      "L = 42.739832, acc = 0.835000\n",
      "L = 42.647161, acc = 0.835000\n",
      "L = 42.556985, acc = 0.835000\n",
      "L = 42.469229, acc = 0.835000\n",
      "L = 42.383824, acc = 0.835000\n",
      "L = 42.300701, acc = 0.835000\n",
      "L = 42.219793, acc = 0.835000\n",
      "L = 42.141037, acc = 0.835000\n",
      "L = 42.064371, acc = 0.835000\n",
      "L = 41.989735, acc = 0.835000\n",
      "L = 41.917070, acc = 0.835000\n",
      "L = 41.846321, acc = 0.840000\n",
      "L = 41.777433, acc = 0.840000\n",
      "L = 41.710353, acc = 0.840000\n",
      "L = 41.645029, acc = 0.840000\n",
      "L = 41.581412, acc = 0.840000\n",
      "L = 41.519453, acc = 0.840000\n",
      "L = 41.459105, acc = 0.840000\n",
      "L = 41.400323, acc = 0.840000\n",
      "L = 41.343062, acc = 0.840000\n",
      "L = 41.287279, acc = 0.845000\n",
      "L = 41.232933, acc = 0.850000\n",
      "L = 41.179982, acc = 0.850000\n",
      "L = 41.128388, acc = 0.855000\n",
      "L = 41.078111, acc = 0.855000\n",
      "L = 41.029115, acc = 0.855000\n",
      "L = 40.981364, acc = 0.855000\n",
      "L = 40.934823, acc = 0.855000\n",
      "L = 40.889456, acc = 0.855000\n",
      "L = 40.845232, acc = 0.855000\n",
      "L = 40.802118, acc = 0.855000\n",
      "L = 40.760083, acc = 0.855000\n",
      "L = 40.719096, acc = 0.855000\n",
      "L = 40.679128, acc = 0.855000\n",
      "L = 40.640150, acc = 0.855000\n",
      "L = 40.602134, acc = 0.855000\n",
      "L = 40.565054, acc = 0.855000\n",
      "L = 40.528883, acc = 0.855000\n",
      "L = 40.493595, acc = 0.855000\n",
      "L = 40.459166, acc = 0.855000\n",
      "L = 40.425572, acc = 0.855000\n",
      "L = 40.392790, acc = 0.855000\n",
      "L = 40.360797, acc = 0.855000\n",
      "L = 40.329570, acc = 0.855000\n",
      "L = 40.299089, acc = 0.855000\n",
      "L = 40.269332, acc = 0.855000\n",
      "L = 40.240281, acc = 0.855000\n",
      "L = 40.211914, acc = 0.855000\n",
      "L = 40.184213, acc = 0.855000\n",
      "L = 40.157160, acc = 0.855000\n",
      "L = 40.130737, acc = 0.855000\n",
      "L = 40.104926, acc = 0.855000\n",
      "L = 40.079711, acc = 0.855000\n",
      "L = 40.055075, acc = 0.855000\n",
      "L = 40.031002, acc = 0.855000\n",
      "L = 40.007477, acc = 0.855000\n",
      "L = 39.984485, acc = 0.855000\n",
      "L = 39.962012, acc = 0.855000\n",
      "L = 39.940043, acc = 0.855000\n",
      "L = 39.918564, acc = 0.855000\n",
      "L = 39.897562, acc = 0.855000\n",
      "L = 39.877025, acc = 0.855000\n",
      "L = 39.856939, acc = 0.855000\n",
      "L = 39.837293, acc = 0.855000\n",
      "L = 39.818074, acc = 0.855000\n",
      "L = 39.799272, acc = 0.855000\n",
      "L = 39.780874, acc = 0.855000\n",
      "L = 39.762871, acc = 0.855000\n",
      "L = 39.745252, acc = 0.855000\n",
      "L = 39.728005, acc = 0.855000\n",
      "L = 39.711123, acc = 0.855000\n",
      "L = 39.694594, acc = 0.855000\n",
      "L = 39.678409, acc = 0.855000\n",
      "L = 39.662560, acc = 0.855000\n",
      "L = 39.647037, acc = 0.855000\n",
      "L = 39.631831, acc = 0.855000\n",
      "L = 39.616936, acc = 0.855000\n",
      "L = 39.602341, acc = 0.855000\n",
      "L = 39.588040, acc = 0.855000\n",
      "L = 39.574025, acc = 0.855000\n",
      "L = 39.560287, acc = 0.855000\n",
      "L = 39.546821, acc = 0.855000\n",
      "L = 39.533619, acc = 0.855000\n",
      "L = 39.520674, acc = 0.855000\n",
      "L = 39.507979, acc = 0.855000\n",
      "L = 39.495528, acc = 0.855000\n",
      "L = 39.483314, acc = 0.855000\n",
      "L = 39.471332, acc = 0.855000\n",
      "L = 39.459575, acc = 0.855000\n",
      "L = 39.448038, acc = 0.855000\n",
      "L = 39.436715, acc = 0.855000\n",
      "L = 39.425601, acc = 0.860000\n",
      "L = 39.414689, acc = 0.860000\n",
      "L = 39.403976, acc = 0.860000\n",
      "L = 39.393455, acc = 0.860000\n",
      "L = 39.383122, acc = 0.860000\n",
      "L = 39.372973, acc = 0.860000\n",
      "L = 39.363001, acc = 0.860000\n",
      "L = 39.353204, acc = 0.860000\n",
      "L = 39.343576, acc = 0.860000\n",
      "L = 39.334113, acc = 0.860000\n",
      "L = 39.324811, acc = 0.860000\n",
      "L = 39.315666, acc = 0.855000\n",
      "L = 39.306674, acc = 0.855000\n",
      "L = 39.297831, acc = 0.855000\n",
      "L = 39.289133, acc = 0.855000\n",
      "L = 39.280576, acc = 0.855000\n",
      "L = 39.272157, acc = 0.850000\n",
      "L = 39.263873, acc = 0.850000\n",
      "L = 39.255720, acc = 0.850000\n",
      "L = 39.247694, acc = 0.850000\n",
      "L = 39.239793, acc = 0.850000\n",
      "L = 39.232013, acc = 0.850000\n",
      "L = 39.224352, acc = 0.850000\n",
      "L = 39.216805, acc = 0.850000\n",
      "L = 39.209371, acc = 0.850000\n",
      "L = 39.202046, acc = 0.850000\n",
      "L = 39.194828, acc = 0.850000\n",
      "L = 39.187713, acc = 0.850000\n",
      "L = 39.180700, acc = 0.850000\n",
      "L = 39.173786, acc = 0.850000\n",
      "L = 39.166968, acc = 0.850000\n",
      "L = 39.160243, acc = 0.850000\n",
      "L = 39.153609, acc = 0.850000\n",
      "L = 39.147065, acc = 0.850000\n",
      "L = 39.140607, acc = 0.850000\n",
      "L = 39.134234, acc = 0.850000\n",
      "L = 39.127943, acc = 0.850000\n",
      "L = 39.121731, acc = 0.850000\n",
      "L = 39.115598, acc = 0.850000\n",
      "L = 39.109541, acc = 0.850000\n",
      "L = 39.103558, acc = 0.850000\n",
      "L = 39.097647, acc = 0.850000\n",
      "L = 39.091806, acc = 0.850000\n",
      "L = 39.086033, acc = 0.850000\n",
      "L = 39.080327, acc = 0.850000\n",
      "L = 39.074685, acc = 0.850000\n",
      "L = 39.069107, acc = 0.850000\n",
      "L = 39.063590, acc = 0.850000\n",
      "L = 39.058132, acc = 0.850000\n",
      "L = 39.052733, acc = 0.850000\n",
      "L = 39.047390, acc = 0.850000\n",
      "L = 39.042101, acc = 0.850000\n",
      "L = 39.036867, acc = 0.850000\n",
      "L = 39.031684, acc = 0.850000\n",
      "L = 39.026552, acc = 0.850000\n",
      "L = 39.021468, acc = 0.850000\n",
      "L = 39.016433, acc = 0.850000\n",
      "L = 39.011443, acc = 0.850000\n",
      "L = 39.006499, acc = 0.850000\n",
      "L = 39.001599, acc = 0.850000\n",
      "L = 38.996740, acc = 0.850000\n",
      "L = 38.991924, acc = 0.850000\n",
      "L = 38.987147, acc = 0.850000\n",
      "L = 38.982408, acc = 0.850000\n",
      "L = 38.977708, acc = 0.850000\n",
      "L = 38.973044, acc = 0.850000\n",
      "L = 38.968415, acc = 0.850000\n",
      "L = 38.963821, acc = 0.850000\n",
      "L = 38.959259, acc = 0.850000\n",
      "L = 38.954730, acc = 0.850000\n",
      "L = 38.950232, acc = 0.850000\n",
      "L = 38.945764, acc = 0.850000\n",
      "L = 38.941325, acc = 0.850000\n",
      "L = 38.936915, acc = 0.850000\n",
      "L = 38.932531, acc = 0.850000\n",
      "L = 38.928174, acc = 0.850000\n",
      "L = 38.923842, acc = 0.850000\n",
      "L = 38.919534, acc = 0.850000\n",
      "L = 38.915250, acc = 0.850000\n",
      "L = 38.910988, acc = 0.850000\n",
      "L = 38.906749, acc = 0.850000\n",
      "L = 38.902530, acc = 0.850000\n",
      "L = 38.898331, acc = 0.850000\n",
      "L = 38.894152, acc = 0.850000\n",
      "L = 38.889991, acc = 0.850000\n",
      "L = 38.885848, acc = 0.850000\n",
      "L = 38.881723, acc = 0.850000\n",
      "L = 38.877613, acc = 0.850000\n",
      "L = 38.873519, acc = 0.850000\n",
      "L = 38.869440, acc = 0.850000\n",
      "L = 38.865374, acc = 0.850000\n",
      "L = 38.861323, acc = 0.850000\n",
      "L = 38.857284, acc = 0.850000\n",
      "L = 38.853257, acc = 0.850000\n",
      "L = 38.849241, acc = 0.850000\n",
      "L = 38.845236, acc = 0.850000\n",
      "L = 38.841241, acc = 0.850000\n",
      "L = 38.837256, acc = 0.850000\n",
      "L = 38.833279, acc = 0.850000\n",
      "L = 38.829311, acc = 0.850000\n",
      "L = 38.825350, acc = 0.850000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 38.821396, acc = 0.850000\n",
      "L = 38.817449, acc = 0.850000\n",
      "L = 38.813507, acc = 0.850000\n",
      "L = 38.809571, acc = 0.850000\n",
      "L = 38.805640, acc = 0.850000\n",
      "L = 38.801713, acc = 0.850000\n",
      "L = 38.797789, acc = 0.850000\n",
      "L = 38.793869, acc = 0.850000\n",
      "L = 38.789951, acc = 0.850000\n",
      "L = 38.786035, acc = 0.850000\n",
      "L = 38.782121, acc = 0.850000\n",
      "L = 38.778208, acc = 0.850000\n",
      "L = 38.774295, acc = 0.850000\n",
      "L = 38.770383, acc = 0.845000\n",
      "L = 38.766470, acc = 0.845000\n",
      "L = 38.762556, acc = 0.845000\n",
      "L = 38.758641, acc = 0.845000\n",
      "L = 38.754724, acc = 0.845000\n",
      "L = 38.750805, acc = 0.845000\n",
      "L = 38.746883, acc = 0.845000\n",
      "L = 38.742958, acc = 0.845000\n",
      "L = 38.739029, acc = 0.845000\n",
      "L = 38.735097, acc = 0.845000\n",
      "L = 38.731160, acc = 0.845000\n",
      "L = 38.727218, acc = 0.845000\n",
      "L = 38.723270, acc = 0.845000\n",
      "L = 38.719317, acc = 0.845000\n",
      "L = 38.715358, acc = 0.845000\n",
      "L = 38.711393, acc = 0.845000\n",
      "L = 38.707420, acc = 0.845000\n",
      "L = 38.703440, acc = 0.845000\n",
      "L = 38.699452, acc = 0.845000\n",
      "L = 38.695456, acc = 0.845000\n",
      "L = 38.691452, acc = 0.845000\n",
      "L = 38.687439, acc = 0.845000\n",
      "L = 38.683416, acc = 0.845000\n",
      "L = 38.679384, acc = 0.845000\n",
      "L = 38.675342, acc = 0.845000\n",
      "L = 38.671290, acc = 0.845000\n",
      "L = 38.667227, acc = 0.845000\n",
      "L = 38.663153, acc = 0.845000\n",
      "L = 38.659067, acc = 0.845000\n",
      "L = 38.654969, acc = 0.845000\n",
      "L = 38.650860, acc = 0.845000\n",
      "L = 38.646738, acc = 0.845000\n",
      "L = 38.642603, acc = 0.845000\n",
      "L = 38.638455, acc = 0.845000\n",
      "L = 38.634293, acc = 0.845000\n",
      "L = 38.630118, acc = 0.845000\n",
      "L = 38.625928, acc = 0.845000\n",
      "L = 38.621724, acc = 0.845000\n",
      "L = 38.617505, acc = 0.845000\n",
      "L = 38.613271, acc = 0.845000\n",
      "L = 38.609021, acc = 0.845000\n",
      "L = 38.604755, acc = 0.845000\n",
      "L = 38.600474, acc = 0.845000\n",
      "L = 38.596176, acc = 0.845000\n",
      "L = 38.591861, acc = 0.845000\n",
      "L = 38.587529, acc = 0.845000\n",
      "L = 38.583179, acc = 0.845000\n",
      "L = 38.578812, acc = 0.845000\n",
      "L = 38.574427, acc = 0.845000\n",
      "L = 38.570023, acc = 0.845000\n",
      "L = 38.565601, acc = 0.845000\n",
      "L = 38.561160, acc = 0.845000\n",
      "L = 38.556699, acc = 0.845000\n",
      "L = 38.552219, acc = 0.845000\n",
      "L = 38.547720, acc = 0.845000\n",
      "L = 38.543199, acc = 0.845000\n",
      "L = 38.538659, acc = 0.845000\n",
      "L = 38.534097, acc = 0.845000\n",
      "L = 38.529515, acc = 0.845000\n",
      "L = 38.524911, acc = 0.845000\n",
      "L = 38.520285, acc = 0.845000\n",
      "L = 38.515638, acc = 0.845000\n",
      "L = 38.510968, acc = 0.845000\n",
      "L = 38.506275, acc = 0.845000\n",
      "L = 38.501560, acc = 0.845000\n",
      "L = 38.496821, acc = 0.845000\n",
      "L = 38.492059, acc = 0.845000\n",
      "L = 38.487273, acc = 0.845000\n",
      "L = 38.482463, acc = 0.845000\n",
      "L = 38.477629, acc = 0.845000\n",
      "L = 38.472770, acc = 0.845000\n",
      "L = 38.467885, acc = 0.845000\n",
      "L = 38.462976, acc = 0.845000\n",
      "L = 38.458041, acc = 0.845000\n",
      "L = 38.453080, acc = 0.845000\n",
      "L = 38.448093, acc = 0.845000\n",
      "L = 38.443079, acc = 0.845000\n",
      "L = 38.438038, acc = 0.845000\n",
      "L = 38.432971, acc = 0.845000\n",
      "L = 38.427876, acc = 0.850000\n",
      "L = 38.422753, acc = 0.850000\n",
      "L = 38.417602, acc = 0.850000\n",
      "L = 38.412423, acc = 0.850000\n",
      "L = 38.407215, acc = 0.850000\n",
      "L = 38.401978, acc = 0.850000\n",
      "L = 38.396712, acc = 0.850000\n",
      "L = 38.391417, acc = 0.850000\n",
      "L = 38.386091, acc = 0.850000\n",
      "L = 38.380735, acc = 0.850000\n",
      "L = 38.375349, acc = 0.850000\n",
      "L = 38.369932, acc = 0.850000\n",
      "L = 38.364484, acc = 0.850000\n",
      "L = 38.359004, acc = 0.850000\n",
      "L = 38.353492, acc = 0.850000\n",
      "L = 38.347948, acc = 0.850000\n",
      "L = 38.342372, acc = 0.850000\n",
      "L = 38.336763, acc = 0.850000\n",
      "L = 38.331121, acc = 0.850000\n",
      "L = 38.325445, acc = 0.850000\n",
      "L = 38.319736, acc = 0.850000\n",
      "L = 38.313992, acc = 0.850000\n",
      "L = 38.308214, acc = 0.850000\n",
      "L = 38.302401, acc = 0.850000\n",
      "L = 38.296553, acc = 0.850000\n",
      "L = 38.290669, acc = 0.850000\n",
      "L = 38.284750, acc = 0.850000\n",
      "L = 38.278794, acc = 0.850000\n",
      "L = 38.272802, acc = 0.850000\n",
      "L = 38.266773, acc = 0.850000\n",
      "L = 38.260706, acc = 0.850000\n",
      "L = 38.254602, acc = 0.850000\n",
      "L = 38.248460, acc = 0.850000\n",
      "L = 38.242279, acc = 0.850000\n",
      "L = 38.236060, acc = 0.850000\n",
      "L = 38.229801, acc = 0.850000\n",
      "L = 38.223503, acc = 0.850000\n",
      "L = 38.217165, acc = 0.850000\n",
      "L = 38.210787, acc = 0.850000\n",
      "L = 38.204368, acc = 0.850000\n",
      "L = 38.197908, acc = 0.850000\n",
      "L = 38.191407, acc = 0.850000\n",
      "L = 38.184864, acc = 0.850000\n",
      "L = 38.178278, acc = 0.850000\n",
      "L = 38.171650, acc = 0.850000\n",
      "L = 38.164978, acc = 0.850000\n",
      "L = 38.158264, acc = 0.850000\n",
      "L = 38.151505, acc = 0.850000\n",
      "L = 38.144702, acc = 0.850000\n",
      "L = 38.137854, acc = 0.850000\n",
      "L = 38.130961, acc = 0.855000\n",
      "L = 38.124022, acc = 0.855000\n",
      "L = 38.117038, acc = 0.855000\n",
      "L = 38.110006, acc = 0.855000\n",
      "L = 38.102928, acc = 0.855000\n",
      "L = 38.095803, acc = 0.855000\n",
      "L = 38.088629, acc = 0.855000\n",
      "L = 38.081407, acc = 0.855000\n",
      "L = 38.074137, acc = 0.855000\n",
      "L = 38.066817, acc = 0.855000\n",
      "L = 38.059448, acc = 0.855000\n",
      "L = 38.052028, acc = 0.855000\n",
      "L = 38.044558, acc = 0.855000\n",
      "L = 38.037036, acc = 0.855000\n",
      "L = 38.029463, acc = 0.855000\n",
      "L = 38.021838, acc = 0.855000\n",
      "L = 38.014160, acc = 0.855000\n",
      "L = 38.006429, acc = 0.855000\n",
      "L = 37.998644, acc = 0.855000\n",
      "L = 37.990805, acc = 0.855000\n",
      "L = 37.982911, acc = 0.855000\n",
      "L = 37.974963, acc = 0.855000\n",
      "L = 37.966958, acc = 0.855000\n",
      "L = 37.958897, acc = 0.855000\n",
      "L = 37.950780, acc = 0.855000\n",
      "L = 37.942605, acc = 0.855000\n",
      "L = 37.934372, acc = 0.855000\n",
      "L = 37.926081, acc = 0.855000\n",
      "L = 37.917730, acc = 0.860000\n",
      "L = 37.909320, acc = 0.860000\n",
      "L = 37.900850, acc = 0.860000\n",
      "L = 37.892320, acc = 0.860000\n",
      "L = 37.883728, acc = 0.860000\n",
      "L = 37.875074, acc = 0.860000\n",
      "L = 37.866357, acc = 0.860000\n",
      "L = 37.857578, acc = 0.860000\n",
      "L = 37.848735, acc = 0.860000\n",
      "L = 37.839827, acc = 0.860000\n",
      "L = 37.830855, acc = 0.860000\n",
      "L = 37.821817, acc = 0.860000\n",
      "L = 37.812713, acc = 0.865000\n",
      "L = 37.803543, acc = 0.865000\n",
      "L = 37.794305, acc = 0.865000\n",
      "L = 37.784999, acc = 0.865000\n",
      "L = 37.775624, acc = 0.865000\n",
      "L = 37.766180, acc = 0.865000\n",
      "L = 37.756666, acc = 0.865000\n",
      "L = 37.747081, acc = 0.865000\n",
      "L = 37.737425, acc = 0.865000\n",
      "L = 37.727698, acc = 0.865000\n",
      "L = 37.717897, acc = 0.865000\n",
      "L = 37.708023, acc = 0.865000\n",
      "L = 37.698075, acc = 0.865000\n",
      "L = 37.688053, acc = 0.865000\n",
      "L = 37.677955, acc = 0.865000\n",
      "L = 37.667781, acc = 0.865000\n",
      "L = 37.657530, acc = 0.865000\n",
      "L = 37.647202, acc = 0.865000\n",
      "L = 37.636795, acc = 0.865000\n",
      "L = 37.626310, acc = 0.865000\n",
      "L = 37.615745, acc = 0.865000\n",
      "L = 37.605099, acc = 0.865000\n",
      "L = 37.594372, acc = 0.865000\n",
      "L = 37.583563, acc = 0.865000\n",
      "L = 37.572672, acc = 0.865000\n",
      "L = 37.561697, acc = 0.865000\n",
      "L = 37.550638, acc = 0.865000\n",
      "L = 37.539494, acc = 0.865000\n",
      "L = 37.528264, acc = 0.865000\n",
      "L = 37.516948, acc = 0.865000\n",
      "L = 37.505544, acc = 0.865000\n",
      "L = 37.494052, acc = 0.865000\n",
      "L = 37.482472, acc = 0.865000\n",
      "L = 37.470801, acc = 0.865000\n",
      "L = 37.459041, acc = 0.865000\n",
      "L = 37.447188, acc = 0.865000\n",
      "L = 37.435244, acc = 0.865000\n",
      "L = 37.423207, acc = 0.865000\n",
      "L = 37.411076, acc = 0.865000\n",
      "L = 37.398851, acc = 0.865000\n",
      "L = 37.386530, acc = 0.865000\n",
      "L = 37.374113, acc = 0.865000\n",
      "L = 37.361598, acc = 0.865000\n",
      "L = 37.348986, acc = 0.865000\n",
      "L = 37.336275, acc = 0.865000\n",
      "L = 37.323464, acc = 0.865000\n",
      "L = 37.310553, acc = 0.865000\n",
      "L = 37.297540, acc = 0.865000\n",
      "L = 37.284425, acc = 0.865000\n",
      "L = 37.271207, acc = 0.865000\n",
      "L = 37.257885, acc = 0.865000\n",
      "L = 37.244458, acc = 0.865000\n",
      "L = 37.230925, acc = 0.865000\n",
      "L = 37.217285, acc = 0.865000\n",
      "L = 37.203538, acc = 0.865000\n",
      "L = 37.189682, acc = 0.865000\n",
      "L = 37.175717, acc = 0.865000\n",
      "L = 37.161642, acc = 0.865000\n",
      "L = 37.147455, acc = 0.865000\n",
      "L = 37.133156, acc = 0.865000\n",
      "L = 37.118744, acc = 0.865000\n",
      "L = 37.104219, acc = 0.865000\n",
      "L = 37.089578, acc = 0.865000\n",
      "L = 37.074821, acc = 0.865000\n",
      "L = 37.059948, acc = 0.865000\n",
      "L = 37.044956, acc = 0.865000\n",
      "L = 37.029847, acc = 0.865000\n",
      "L = 37.014617, acc = 0.865000\n",
      "L = 36.999267, acc = 0.865000\n",
      "L = 36.983795, acc = 0.865000\n",
      "L = 36.968201, acc = 0.865000\n",
      "L = 36.952484, acc = 0.865000\n",
      "L = 36.936642, acc = 0.865000\n",
      "L = 36.920675, acc = 0.865000\n",
      "L = 36.904581, acc = 0.865000\n",
      "L = 36.888361, acc = 0.865000\n",
      "L = 36.872012, acc = 0.865000\n",
      "L = 36.855533, acc = 0.865000\n",
      "L = 36.838925, acc = 0.865000\n",
      "L = 36.822185, acc = 0.865000\n",
      "L = 36.805314, acc = 0.865000\n",
      "L = 36.788309, acc = 0.865000\n",
      "L = 36.771170, acc = 0.865000\n",
      "L = 36.753896, acc = 0.865000\n",
      "L = 36.736486, acc = 0.865000\n",
      "L = 36.718939, acc = 0.865000\n",
      "L = 36.701254, acc = 0.865000\n",
      "L = 36.683429, acc = 0.865000\n",
      "L = 36.665465, acc = 0.865000\n",
      "L = 36.647360, acc = 0.865000\n",
      "L = 36.629113, acc = 0.865000\n",
      "L = 36.610723, acc = 0.865000\n",
      "L = 36.592189, acc = 0.865000\n",
      "L = 36.573510, acc = 0.865000\n",
      "L = 36.554686, acc = 0.865000\n",
      "L = 36.535714, acc = 0.865000\n",
      "L = 36.516595, acc = 0.865000\n",
      "L = 36.497326, acc = 0.865000\n",
      "L = 36.477908, acc = 0.865000\n",
      "L = 36.458339, acc = 0.865000\n",
      "L = 36.438618, acc = 0.865000\n",
      "L = 36.418744, acc = 0.865000\n",
      "L = 36.398717, acc = 0.865000\n",
      "L = 36.378534, acc = 0.865000\n",
      "L = 36.358196, acc = 0.865000\n",
      "L = 36.337701, acc = 0.865000\n",
      "L = 36.317049, acc = 0.865000\n",
      "L = 36.296238, acc = 0.865000\n",
      "L = 36.275267, acc = 0.865000\n",
      "L = 36.254136, acc = 0.865000\n",
      "L = 36.232843, acc = 0.865000\n",
      "L = 36.211387, acc = 0.865000\n",
      "L = 36.189768, acc = 0.865000\n",
      "L = 36.167985, acc = 0.870000\n",
      "L = 36.146036, acc = 0.870000\n",
      "L = 36.123921, acc = 0.870000\n",
      "L = 36.101638, acc = 0.870000\n",
      "L = 36.079188, acc = 0.870000\n",
      "L = 36.056568, acc = 0.870000\n",
      "L = 36.033778, acc = 0.870000\n",
      "L = 36.010817, acc = 0.870000\n",
      "L = 35.987684, acc = 0.870000\n",
      "L = 35.964378, acc = 0.870000\n",
      "L = 35.940898, acc = 0.870000\n",
      "L = 35.917243, acc = 0.870000\n",
      "L = 35.893413, acc = 0.870000\n",
      "L = 35.869407, acc = 0.870000\n",
      "L = 35.845223, acc = 0.870000\n",
      "L = 35.820860, acc = 0.870000\n",
      "L = 35.796319, acc = 0.870000\n",
      "L = 35.771597, acc = 0.870000\n",
      "L = 35.746695, acc = 0.870000\n",
      "L = 35.721610, acc = 0.870000\n",
      "L = 35.696343, acc = 0.870000\n",
      "L = 35.670893, acc = 0.870000\n",
      "L = 35.645258, acc = 0.870000\n",
      "L = 35.619438, acc = 0.870000\n",
      "L = 35.593432, acc = 0.870000\n",
      "L = 35.567239, acc = 0.870000\n",
      "L = 35.540859, acc = 0.870000\n",
      "L = 35.514290, acc = 0.875000\n",
      "L = 35.487532, acc = 0.875000\n",
      "L = 35.460584, acc = 0.875000\n",
      "L = 35.433445, acc = 0.875000\n",
      "L = 35.406115, acc = 0.875000\n",
      "L = 35.378593, acc = 0.875000\n",
      "L = 35.350877, acc = 0.875000\n",
      "L = 35.322968, acc = 0.875000\n",
      "L = 35.294864, acc = 0.875000\n",
      "L = 35.266565, acc = 0.875000\n",
      "L = 35.238070, acc = 0.875000\n",
      "L = 35.209379, acc = 0.875000\n",
      "L = 35.180490, acc = 0.875000\n",
      "L = 35.151403, acc = 0.875000\n",
      "L = 35.122118, acc = 0.875000\n",
      "L = 35.092634, acc = 0.875000\n",
      "L = 35.062950, acc = 0.875000\n",
      "L = 35.033065, acc = 0.875000\n",
      "L = 35.002979, acc = 0.875000\n",
      "L = 34.972691, acc = 0.875000\n",
      "L = 34.942202, acc = 0.875000\n",
      "L = 34.911509, acc = 0.875000\n",
      "L = 34.880613, acc = 0.875000\n",
      "L = 34.849513, acc = 0.875000\n",
      "L = 34.818209, acc = 0.875000\n",
      "L = 34.786700, acc = 0.875000\n",
      "L = 34.754985, acc = 0.875000\n",
      "L = 34.723064, acc = 0.875000\n",
      "L = 34.690937, acc = 0.875000\n",
      "L = 34.658603, acc = 0.875000\n",
      "L = 34.626062, acc = 0.875000\n",
      "L = 34.593313, acc = 0.875000\n",
      "L = 34.560356, acc = 0.875000\n",
      "L = 34.527191, acc = 0.875000\n",
      "L = 34.493817, acc = 0.875000\n",
      "L = 34.460233, acc = 0.875000\n",
      "L = 34.426440, acc = 0.875000\n",
      "L = 34.392437, acc = 0.875000\n",
      "L = 34.358224, acc = 0.880000\n",
      "L = 34.323801, acc = 0.880000\n",
      "L = 34.289167, acc = 0.880000\n",
      "L = 34.254322, acc = 0.880000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 34.219266, acc = 0.880000\n",
      "L = 34.183998, acc = 0.880000\n",
      "L = 34.148519, acc = 0.880000\n",
      "L = 34.112828, acc = 0.880000\n",
      "L = 34.076926, acc = 0.880000\n",
      "L = 34.040811, acc = 0.885000\n",
      "L = 34.004484, acc = 0.885000\n",
      "L = 33.967945, acc = 0.885000\n",
      "L = 33.931194, acc = 0.885000\n",
      "L = 33.894230, acc = 0.885000\n",
      "L = 33.857054, acc = 0.890000\n",
      "L = 33.819666, acc = 0.890000\n",
      "L = 33.782065, acc = 0.890000\n",
      "L = 33.744252, acc = 0.895000\n",
      "L = 33.706227, acc = 0.895000\n",
      "L = 33.667990, acc = 0.895000\n",
      "L = 33.629540, acc = 0.895000\n",
      "L = 33.590879, acc = 0.895000\n",
      "L = 33.552006, acc = 0.895000\n",
      "L = 33.512921, acc = 0.895000\n",
      "L = 33.473625, acc = 0.895000\n",
      "L = 33.434117, acc = 0.895000\n",
      "L = 33.394399, acc = 0.895000\n",
      "L = 33.354470, acc = 0.895000\n",
      "L = 33.314330, acc = 0.895000\n",
      "L = 33.273981, acc = 0.895000\n",
      "L = 33.233421, acc = 0.895000\n",
      "L = 33.192652, acc = 0.895000\n",
      "L = 33.151675, acc = 0.895000\n",
      "L = 33.110488, acc = 0.895000\n",
      "L = 33.069093, acc = 0.900000\n",
      "L = 33.027491, acc = 0.900000\n",
      "L = 32.985681, acc = 0.900000\n",
      "L = 32.943664, acc = 0.900000\n",
      "L = 32.901441, acc = 0.900000\n",
      "L = 32.859013, acc = 0.900000\n",
      "L = 32.816379, acc = 0.900000\n",
      "L = 32.773541, acc = 0.900000\n",
      "L = 32.730499, acc = 0.900000\n",
      "L = 32.687253, acc = 0.900000\n",
      "L = 32.643806, acc = 0.900000\n",
      "L = 32.600156, acc = 0.900000\n",
      "L = 32.556305, acc = 0.900000\n",
      "L = 32.512253, acc = 0.900000\n",
      "L = 32.468002, acc = 0.900000\n",
      "L = 32.423553, acc = 0.900000\n",
      "L = 32.378905, acc = 0.900000\n",
      "L = 32.334060, acc = 0.900000\n",
      "L = 32.289019, acc = 0.900000\n",
      "L = 32.243782, acc = 0.900000\n",
      "L = 32.198351, acc = 0.900000\n",
      "L = 32.152726, acc = 0.900000\n",
      "L = 32.106909, acc = 0.900000\n",
      "L = 32.060901, acc = 0.900000\n",
      "L = 32.014702, acc = 0.900000\n",
      "L = 31.968314, acc = 0.900000\n",
      "L = 31.921737, acc = 0.900000\n",
      "L = 31.874973, acc = 0.900000\n",
      "L = 31.828023, acc = 0.900000\n",
      "L = 31.780887, acc = 0.900000\n",
      "L = 31.733569, acc = 0.900000\n",
      "L = 31.686067, acc = 0.900000\n",
      "L = 31.638384, acc = 0.900000\n",
      "L = 31.590521, acc = 0.900000\n",
      "L = 31.542479, acc = 0.900000\n",
      "L = 31.494260, acc = 0.900000\n",
      "L = 31.445864, acc = 0.900000\n",
      "L = 31.397293, acc = 0.900000\n",
      "L = 31.348549, acc = 0.905000\n",
      "L = 31.299632, acc = 0.905000\n",
      "L = 31.250545, acc = 0.905000\n",
      "L = 31.201289, acc = 0.905000\n",
      "L = 31.151864, acc = 0.905000\n",
      "L = 31.102273, acc = 0.905000\n",
      "L = 31.052517, acc = 0.905000\n",
      "L = 31.002598, acc = 0.905000\n",
      "L = 30.952517, acc = 0.905000\n",
      "L = 30.902276, acc = 0.905000\n",
      "L = 30.851875, acc = 0.905000\n",
      "L = 30.801318, acc = 0.905000\n",
      "L = 30.750605, acc = 0.905000\n",
      "L = 30.699738, acc = 0.905000\n",
      "L = 30.648719, acc = 0.905000\n",
      "L = 30.597550, acc = 0.905000\n",
      "L = 30.546231, acc = 0.905000\n",
      "L = 30.494766, acc = 0.905000\n",
      "L = 30.443155, acc = 0.905000\n",
      "L = 30.391400, acc = 0.905000\n",
      "L = 30.339503, acc = 0.905000\n",
      "L = 30.287466, acc = 0.910000\n",
      "L = 30.235291, acc = 0.910000\n",
      "L = 30.182980, acc = 0.910000\n",
      "L = 30.130533, acc = 0.910000\n",
      "L = 30.077954, acc = 0.910000\n",
      "L = 30.025244, acc = 0.910000\n",
      "L = 29.972404, acc = 0.910000\n",
      "L = 29.919438, acc = 0.910000\n",
      "L = 29.866346, acc = 0.910000\n",
      "L = 29.813130, acc = 0.910000\n",
      "L = 29.759793, acc = 0.910000\n",
      "L = 29.706337, acc = 0.910000\n",
      "L = 29.652763, acc = 0.910000\n",
      "L = 29.599073, acc = 0.910000\n",
      "L = 29.545270, acc = 0.910000\n",
      "L = 29.491355, acc = 0.910000\n",
      "L = 29.437330, acc = 0.910000\n",
      "L = 29.383198, acc = 0.910000\n",
      "L = 29.328960, acc = 0.910000\n",
      "L = 29.274619, acc = 0.910000\n",
      "L = 29.220176, acc = 0.910000\n",
      "L = 29.165633, acc = 0.910000\n",
      "L = 29.110993, acc = 0.910000\n",
      "L = 29.056258, acc = 0.910000\n",
      "L = 29.001430, acc = 0.910000\n",
      "L = 28.946510, acc = 0.910000\n",
      "L = 28.891501, acc = 0.910000\n",
      "L = 28.836405, acc = 0.910000\n",
      "L = 28.781224, acc = 0.910000\n",
      "L = 28.725960, acc = 0.910000\n",
      "L = 28.670616, acc = 0.910000\n",
      "L = 28.615193, acc = 0.910000\n",
      "L = 28.559693, acc = 0.910000\n",
      "L = 28.504119, acc = 0.910000\n",
      "L = 28.448473, acc = 0.915000\n",
      "L = 28.392757, acc = 0.915000\n",
      "L = 28.336973, acc = 0.915000\n",
      "L = 28.281123, acc = 0.915000\n",
      "L = 28.225209, acc = 0.915000\n",
      "L = 28.169234, acc = 0.915000\n",
      "L = 28.113200, acc = 0.915000\n",
      "L = 28.057108, acc = 0.915000\n",
      "L = 28.000962, acc = 0.915000\n",
      "L = 27.944762, acc = 0.915000\n",
      "L = 27.888512, acc = 0.915000\n",
      "L = 27.832213, acc = 0.915000\n",
      "L = 27.775868, acc = 0.915000\n",
      "L = 27.719478, acc = 0.915000\n",
      "L = 27.663046, acc = 0.920000\n",
      "L = 27.606575, acc = 0.920000\n",
      "L = 27.550065, acc = 0.920000\n",
      "L = 27.493520, acc = 0.920000\n",
      "L = 27.436941, acc = 0.920000\n",
      "L = 27.380331, acc = 0.920000\n",
      "L = 27.323692, acc = 0.920000\n",
      "L = 27.267026, acc = 0.920000\n",
      "L = 27.210335, acc = 0.920000\n",
      "L = 27.153621, acc = 0.920000\n",
      "L = 27.096886, acc = 0.920000\n",
      "L = 27.040133, acc = 0.920000\n",
      "L = 26.983363, acc = 0.920000\n",
      "L = 26.926579, acc = 0.920000\n",
      "L = 26.869783, acc = 0.920000\n",
      "L = 26.812977, acc = 0.920000\n",
      "L = 26.756163, acc = 0.920000\n",
      "L = 26.699343, acc = 0.920000\n",
      "L = 26.642520, acc = 0.920000\n",
      "L = 26.585694, acc = 0.920000\n",
      "L = 26.528870, acc = 0.920000\n",
      "L = 26.472048, acc = 0.920000\n",
      "L = 26.415230, acc = 0.925000\n",
      "L = 26.358420, acc = 0.925000\n",
      "L = 26.301618, acc = 0.925000\n",
      "L = 26.244827, acc = 0.925000\n",
      "L = 26.188049, acc = 0.925000\n",
      "L = 26.131286, acc = 0.925000\n",
      "L = 26.074540, acc = 0.925000\n",
      "L = 26.017813, acc = 0.925000\n",
      "L = 25.961107, acc = 0.925000\n",
      "L = 25.904425, acc = 0.925000\n",
      "L = 25.847767, acc = 0.925000\n",
      "L = 25.791137, acc = 0.925000\n",
      "L = 25.734536, acc = 0.925000\n",
      "L = 25.677966, acc = 0.925000\n",
      "L = 25.621429, acc = 0.925000\n",
      "L = 25.564927, acc = 0.925000\n",
      "L = 25.508462, acc = 0.925000\n",
      "L = 25.452037, acc = 0.925000\n",
      "L = 25.395652, acc = 0.925000\n",
      "L = 25.339311, acc = 0.925000\n",
      "L = 25.283014, acc = 0.925000\n",
      "L = 25.226764, acc = 0.925000\n",
      "L = 25.170563, acc = 0.925000\n",
      "L = 25.114413, acc = 0.925000\n",
      "L = 25.058315, acc = 0.925000\n",
      "L = 25.002272, acc = 0.925000\n",
      "L = 24.946285, acc = 0.925000\n",
      "L = 24.890356, acc = 0.925000\n",
      "L = 24.834487, acc = 0.925000\n",
      "L = 24.778680, acc = 0.925000\n",
      "L = 24.722937, acc = 0.925000\n",
      "L = 24.667260, acc = 0.925000\n",
      "L = 24.611650, acc = 0.925000\n",
      "L = 24.556109, acc = 0.925000\n",
      "L = 24.500639, acc = 0.925000\n",
      "L = 24.445243, acc = 0.930000\n",
      "L = 24.389920, acc = 0.930000\n",
      "L = 24.334674, acc = 0.930000\n",
      "L = 24.279506, acc = 0.930000\n",
      "L = 24.224418, acc = 0.930000\n",
      "L = 24.169412, acc = 0.930000\n",
      "L = 24.114489, acc = 0.930000\n",
      "L = 24.059651, acc = 0.930000\n",
      "L = 24.004900, acc = 0.930000\n",
      "L = 23.950237, acc = 0.930000\n",
      "L = 23.895664, acc = 0.935000\n",
      "L = 23.841183, acc = 0.935000\n",
      "L = 23.786795, acc = 0.935000\n",
      "L = 23.732502, acc = 0.935000\n",
      "L = 23.678306, acc = 0.935000\n",
      "L = 23.624208, acc = 0.935000\n",
      "L = 23.570210, acc = 0.935000\n",
      "L = 23.516313, acc = 0.935000\n",
      "L = 23.462519, acc = 0.935000\n",
      "L = 23.408830, acc = 0.935000\n",
      "L = 23.355246, acc = 0.935000\n",
      "L = 23.301771, acc = 0.935000\n",
      "L = 23.248404, acc = 0.935000\n",
      "L = 23.195148, acc = 0.935000\n",
      "L = 23.142004, acc = 0.935000\n",
      "L = 23.088973, acc = 0.935000\n",
      "L = 23.036058, acc = 0.935000\n",
      "L = 22.983258, acc = 0.935000\n",
      "L = 22.930577, acc = 0.935000\n",
      "L = 22.878015, acc = 0.935000\n",
      "L = 22.825573, acc = 0.940000\n",
      "L = 22.773253, acc = 0.940000\n",
      "L = 22.721057, acc = 0.940000\n",
      "L = 22.668985, acc = 0.940000\n",
      "L = 22.617039, acc = 0.940000\n",
      "L = 22.565221, acc = 0.940000\n",
      "L = 22.513531, acc = 0.940000\n",
      "L = 22.461971, acc = 0.940000\n",
      "L = 22.410542, acc = 0.940000\n",
      "L = 22.359245, acc = 0.940000\n",
      "L = 22.308082, acc = 0.940000\n",
      "L = 22.257054, acc = 0.940000\n",
      "L = 22.206161, acc = 0.940000\n",
      "L = 22.155406, acc = 0.940000\n",
      "L = 22.104789, acc = 0.940000\n",
      "L = 22.054312, acc = 0.940000\n",
      "L = 22.003975, acc = 0.940000\n",
      "L = 21.953779, acc = 0.940000\n",
      "L = 21.903726, acc = 0.940000\n",
      "L = 21.853818, acc = 0.940000\n",
      "L = 21.804053, acc = 0.945000\n",
      "L = 21.754435, acc = 0.945000\n",
      "L = 21.704964, acc = 0.945000\n",
      "L = 21.655640, acc = 0.945000\n",
      "L = 21.606465, acc = 0.945000\n",
      "L = 21.557440, acc = 0.945000\n",
      "L = 21.508566, acc = 0.945000\n",
      "L = 21.459843, acc = 0.945000\n",
      "L = 21.411273, acc = 0.945000\n",
      "L = 21.362856, acc = 0.945000\n",
      "L = 21.314594, acc = 0.945000\n",
      "L = 21.266486, acc = 0.945000\n",
      "L = 21.218535, acc = 0.945000\n",
      "L = 21.170740, acc = 0.945000\n",
      "L = 21.123103, acc = 0.945000\n",
      "L = 21.075623, acc = 0.945000\n",
      "L = 21.028303, acc = 0.945000\n",
      "L = 20.981143, acc = 0.945000\n",
      "L = 20.934143, acc = 0.945000\n",
      "L = 20.887304, acc = 0.945000\n",
      "L = 20.840627, acc = 0.945000\n",
      "L = 20.794113, acc = 0.945000\n",
      "L = 20.747761, acc = 0.945000\n",
      "L = 20.701573, acc = 0.945000\n",
      "L = 20.655550, acc = 0.945000\n",
      "L = 20.609691, acc = 0.945000\n",
      "L = 20.563998, acc = 0.945000\n",
      "L = 20.518470, acc = 0.945000\n",
      "L = 20.473109, acc = 0.945000\n",
      "L = 20.427915, acc = 0.945000\n",
      "L = 20.382889, acc = 0.945000\n",
      "L = 20.338030, acc = 0.945000\n",
      "L = 20.293339, acc = 0.945000\n",
      "L = 20.248818, acc = 0.945000\n",
      "L = 20.204465, acc = 0.945000\n",
      "L = 20.160282, acc = 0.945000\n",
      "L = 20.116268, acc = 0.945000\n",
      "L = 20.072425, acc = 0.945000\n",
      "L = 20.028753, acc = 0.945000\n",
      "L = 19.985251, acc = 0.945000\n",
      "L = 19.941921, acc = 0.945000\n",
      "L = 19.898762, acc = 0.945000\n",
      "L = 19.855774, acc = 0.945000\n",
      "L = 19.812959, acc = 0.945000\n",
      "L = 19.770315, acc = 0.945000\n",
      "L = 19.727844, acc = 0.945000\n",
      "L = 19.685545, acc = 0.945000\n",
      "L = 19.643419, acc = 0.945000\n",
      "L = 19.601466, acc = 0.945000\n",
      "L = 19.559686, acc = 0.945000\n",
      "L = 19.518079, acc = 0.945000\n",
      "L = 19.476645, acc = 0.945000\n",
      "L = 19.435384, acc = 0.945000\n",
      "L = 19.394297, acc = 0.945000\n",
      "L = 19.353382, acc = 0.945000\n",
      "L = 19.312642, acc = 0.945000\n",
      "L = 19.272074, acc = 0.945000\n",
      "L = 19.231680, acc = 0.945000\n",
      "L = 19.191460, acc = 0.945000\n",
      "L = 19.151412, acc = 0.945000\n",
      "L = 19.111538, acc = 0.945000\n",
      "L = 19.071837, acc = 0.945000\n",
      "L = 19.032310, acc = 0.945000\n",
      "L = 18.992955, acc = 0.945000\n",
      "L = 18.953773, acc = 0.945000\n",
      "L = 18.914764, acc = 0.945000\n",
      "L = 18.875928, acc = 0.945000\n",
      "L = 18.837265, acc = 0.945000\n",
      "L = 18.798773, acc = 0.945000\n",
      "L = 18.760454, acc = 0.945000\n",
      "L = 18.722307, acc = 0.945000\n",
      "L = 18.684332, acc = 0.945000\n",
      "L = 18.646528, acc = 0.945000\n",
      "L = 18.608895, acc = 0.945000\n",
      "L = 18.571434, acc = 0.945000\n",
      "L = 18.534143, acc = 0.945000\n",
      "L = 18.497023, acc = 0.945000\n",
      "L = 18.460074, acc = 0.945000\n",
      "L = 18.423294, acc = 0.945000\n",
      "L = 18.386684, acc = 0.945000\n",
      "L = 18.350243, acc = 0.945000\n",
      "L = 18.313971, acc = 0.945000\n",
      "L = 18.277868, acc = 0.945000\n",
      "L = 18.241934, acc = 0.945000\n",
      "L = 18.206167, acc = 0.945000\n",
      "L = 18.170568, acc = 0.945000\n",
      "L = 18.135136, acc = 0.945000\n",
      "L = 18.099871, acc = 0.945000\n",
      "L = 18.064772, acc = 0.950000\n",
      "L = 18.029840, acc = 0.950000\n",
      "L = 17.995073, acc = 0.950000\n",
      "L = 17.960471, acc = 0.950000\n",
      "L = 17.926034, acc = 0.950000\n",
      "L = 17.891761, acc = 0.950000\n",
      "L = 17.857652, acc = 0.950000\n",
      "L = 17.823706, acc = 0.950000\n",
      "L = 17.789924, acc = 0.950000\n",
      "L = 17.756303, acc = 0.950000\n",
      "L = 17.722845, acc = 0.950000\n",
      "L = 17.689548, acc = 0.950000\n",
      "L = 17.656412, acc = 0.950000\n",
      "L = 17.623436, acc = 0.950000\n",
      "L = 17.590620, acc = 0.955000\n",
      "L = 17.557963, acc = 0.955000\n",
      "L = 17.525466, acc = 0.955000\n",
      "L = 17.493126, acc = 0.955000\n",
      "L = 17.460945, acc = 0.955000\n",
      "L = 17.428920, acc = 0.955000\n",
      "L = 17.397052, acc = 0.955000\n",
      "L = 17.365340, acc = 0.955000\n",
      "L = 17.333784, acc = 0.955000\n",
      "L = 17.302383, acc = 0.955000\n",
      "L = 17.271136, acc = 0.955000\n",
      "L = 17.240043, acc = 0.955000\n",
      "L = 17.209102, acc = 0.955000\n",
      "L = 17.178315, acc = 0.955000\n",
      "L = 17.147679, acc = 0.955000\n",
      "L = 17.117195, acc = 0.955000\n",
      "L = 17.086862, acc = 0.955000\n",
      "L = 17.056679, acc = 0.955000\n",
      "L = 17.026645, acc = 0.955000\n",
      "L = 16.996760, acc = 0.955000\n",
      "L = 16.967024, acc = 0.955000\n",
      "L = 16.937435, acc = 0.955000\n",
      "L = 16.907994, acc = 0.955000\n",
      "L = 16.878698, acc = 0.955000\n",
      "L = 16.849549, acc = 0.955000\n",
      "L = 16.820545, acc = 0.955000\n",
      "L = 16.791685, acc = 0.955000\n",
      "L = 16.762969, acc = 0.955000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 16.734396, acc = 0.955000\n",
      "L = 16.705966, acc = 0.955000\n",
      "L = 16.677678, acc = 0.955000\n",
      "L = 16.649531, acc = 0.955000\n",
      "L = 16.621525, acc = 0.955000\n",
      "L = 16.593659, acc = 0.955000\n",
      "L = 16.565932, acc = 0.955000\n",
      "L = 16.538343, acc = 0.955000\n",
      "L = 16.510893, acc = 0.955000\n",
      "L = 16.483580, acc = 0.955000\n",
      "L = 16.456404, acc = 0.955000\n",
      "L = 16.429364, acc = 0.955000\n",
      "L = 16.402459, acc = 0.955000\n",
      "L = 16.375689, acc = 0.955000\n",
      "L = 16.349053, acc = 0.955000\n",
      "L = 16.322550, acc = 0.955000\n",
      "L = 16.296180, acc = 0.955000\n",
      "L = 16.269942, acc = 0.955000\n",
      "L = 16.243835, acc = 0.955000\n",
      "L = 16.217859, acc = 0.955000\n",
      "L = 16.192013, acc = 0.955000\n",
      "L = 16.166297, acc = 0.955000\n",
      "L = 16.140709, acc = 0.955000\n",
      "L = 16.115249, acc = 0.955000\n",
      "L = 16.089917, acc = 0.955000\n",
      "L = 16.064711, acc = 0.955000\n",
      "L = 16.039632, acc = 0.955000\n",
      "L = 16.014677, acc = 0.955000\n",
      "L = 15.989848, acc = 0.955000\n",
      "L = 15.965142, acc = 0.955000\n",
      "L = 15.940560, acc = 0.955000\n",
      "L = 15.916101, acc = 0.955000\n",
      "L = 15.891764, acc = 0.955000\n",
      "L = 15.867548, acc = 0.955000\n",
      "L = 15.843453, acc = 0.955000\n",
      "L = 15.819478, acc = 0.955000\n",
      "L = 15.795622, acc = 0.955000\n",
      "L = 15.771886, acc = 0.955000\n",
      "L = 15.748267, acc = 0.955000\n",
      "L = 15.724766, acc = 0.955000\n",
      "L = 15.701382, acc = 0.955000\n",
      "L = 15.678114, acc = 0.955000\n",
      "L = 15.654961, acc = 0.955000\n",
      "L = 15.631923, acc = 0.955000\n",
      "L = 15.609000, acc = 0.955000\n",
      "L = 15.586190, acc = 0.955000\n",
      "L = 15.563493, acc = 0.955000\n",
      "L = 15.540909, acc = 0.955000\n",
      "L = 15.518436, acc = 0.955000\n",
      "L = 15.496074, acc = 0.955000\n",
      "L = 15.473823, acc = 0.955000\n",
      "L = 15.451681, acc = 0.955000\n",
      "L = 15.429649, acc = 0.955000\n",
      "L = 15.407725, acc = 0.960000\n",
      "L = 15.385909, acc = 0.960000\n",
      "L = 15.364200, acc = 0.960000\n",
      "L = 15.342598, acc = 0.960000\n",
      "L = 15.321102, acc = 0.960000\n",
      "L = 15.299711, acc = 0.960000\n",
      "L = 15.278425, acc = 0.960000\n",
      "L = 15.257244, acc = 0.960000\n",
      "L = 15.236166, acc = 0.960000\n",
      "L = 15.215191, acc = 0.960000\n",
      "L = 15.194318, acc = 0.960000\n",
      "L = 15.173547, acc = 0.960000\n",
      "L = 15.152877, acc = 0.960000\n",
      "L = 15.132308, acc = 0.960000\n",
      "L = 15.111839, acc = 0.960000\n",
      "L = 15.091469, acc = 0.960000\n",
      "L = 15.071198, acc = 0.960000\n",
      "L = 15.051025, acc = 0.960000\n",
      "L = 15.030950, acc = 0.960000\n",
      "L = 15.010972, acc = 0.960000\n",
      "L = 14.991090, acc = 0.960000\n",
      "L = 14.971304, acc = 0.960000\n",
      "L = 14.951614, acc = 0.960000\n",
      "L = 14.932018, acc = 0.960000\n",
      "L = 14.912516, acc = 0.960000\n",
      "L = 14.893108, acc = 0.960000\n",
      "L = 14.873793, acc = 0.960000\n",
      "L = 14.854571, acc = 0.960000\n",
      "L = 14.835440, acc = 0.960000\n",
      "L = 14.816401, acc = 0.960000\n",
      "L = 14.797452, acc = 0.960000\n",
      "L = 14.778594, acc = 0.960000\n",
      "L = 14.759825, acc = 0.960000\n",
      "L = 14.741146, acc = 0.960000\n",
      "L = 14.722555, acc = 0.960000\n",
      "L = 14.704052, acc = 0.960000\n",
      "L = 14.685637, acc = 0.960000\n",
      "L = 14.667308, acc = 0.960000\n",
      "L = 14.649067, acc = 0.960000\n",
      "L = 14.630911, acc = 0.960000\n",
      "L = 14.612840, acc = 0.960000\n",
      "L = 14.594854, acc = 0.960000\n",
      "L = 14.576953, acc = 0.960000\n",
      "L = 14.559136, acc = 0.960000\n",
      "L = 14.541402, acc = 0.960000\n",
      "L = 14.523750, acc = 0.960000\n",
      "L = 14.506181, acc = 0.960000\n",
      "L = 14.488694, acc = 0.960000\n",
      "L = 14.471288, acc = 0.960000\n",
      "L = 14.453963, acc = 0.960000\n",
      "L = 14.436718, acc = 0.960000\n",
      "L = 14.419553, acc = 0.960000\n",
      "L = 14.402467, acc = 0.960000\n",
      "L = 14.385460, acc = 0.960000\n",
      "L = 14.368532, acc = 0.960000\n",
      "L = 14.351681, acc = 0.960000\n",
      "L = 14.334907, acc = 0.960000\n",
      "L = 14.318211, acc = 0.960000\n",
      "L = 14.301591, acc = 0.960000\n",
      "L = 14.285046, acc = 0.960000\n",
      "L = 14.268578, acc = 0.960000\n",
      "L = 14.252184, acc = 0.960000\n",
      "L = 14.235864, acc = 0.960000\n",
      "L = 14.219619, acc = 0.960000\n",
      "L = 14.203448, acc = 0.960000\n",
      "L = 14.187349, acc = 0.960000\n",
      "L = 14.171323, acc = 0.960000\n",
      "L = 14.155370, acc = 0.960000\n",
      "L = 14.139488, acc = 0.960000\n",
      "L = 14.123677, acc = 0.960000\n",
      "L = 14.107938, acc = 0.960000\n",
      "L = 14.092268, acc = 0.960000\n",
      "L = 14.076669, acc = 0.960000\n",
      "L = 14.061140, acc = 0.960000\n",
      "L = 14.045679, acc = 0.960000\n",
      "L = 14.030288, acc = 0.960000\n",
      "L = 14.014964, acc = 0.960000\n",
      "L = 13.999708, acc = 0.960000\n",
      "L = 13.984520, acc = 0.960000\n",
      "L = 13.969399, acc = 0.960000\n",
      "L = 13.954345, acc = 0.960000\n",
      "L = 13.939356, acc = 0.960000\n",
      "L = 13.924434, acc = 0.960000\n",
      "L = 13.909576, acc = 0.960000\n",
      "L = 13.894784, acc = 0.960000\n",
      "L = 13.880056, acc = 0.960000\n",
      "L = 13.865393, acc = 0.960000\n",
      "L = 13.850793, acc = 0.960000\n",
      "L = 13.836256, acc = 0.960000\n",
      "L = 13.821783, acc = 0.960000\n",
      "L = 13.807372, acc = 0.960000\n",
      "L = 13.793023, acc = 0.960000\n",
      "L = 13.778736, acc = 0.960000\n",
      "L = 13.764510, acc = 0.960000\n",
      "L = 13.750345, acc = 0.960000\n",
      "L = 13.736241, acc = 0.960000\n",
      "L = 13.722198, acc = 0.960000\n",
      "L = 13.708214, acc = 0.960000\n",
      "L = 13.694289, acc = 0.960000\n",
      "L = 13.680424, acc = 0.960000\n",
      "L = 13.666618, acc = 0.960000\n",
      "L = 13.652869, acc = 0.960000\n",
      "L = 13.639179, acc = 0.960000\n",
      "L = 13.625547, acc = 0.960000\n",
      "L = 13.611972, acc = 0.960000\n",
      "L = 13.598454, acc = 0.960000\n",
      "L = 13.584992, acc = 0.960000\n",
      "L = 13.571587, acc = 0.960000\n",
      "L = 13.558238, acc = 0.960000\n",
      "L = 13.544944, acc = 0.960000\n",
      "L = 13.531706, acc = 0.960000\n",
      "L = 13.518522, acc = 0.960000\n",
      "L = 13.505393, acc = 0.960000\n",
      "L = 13.492318, acc = 0.960000\n",
      "L = 13.479297, acc = 0.960000\n",
      "L = 13.466330, acc = 0.960000\n",
      "L = 13.453415, acc = 0.960000\n",
      "L = 13.440554, acc = 0.960000\n",
      "L = 13.427745, acc = 0.960000\n",
      "L = 13.414988, acc = 0.960000\n",
      "L = 13.402284, acc = 0.960000\n",
      "L = 13.389630, acc = 0.960000\n",
      "L = 13.377028, acc = 0.960000\n",
      "L = 13.364477, acc = 0.960000\n",
      "L = 13.351977, acc = 0.960000\n",
      "L = 13.339527, acc = 0.960000\n",
      "L = 13.327127, acc = 0.960000\n",
      "L = 13.314776, acc = 0.960000\n",
      "L = 13.302475, acc = 0.960000\n",
      "L = 13.290223, acc = 0.960000\n",
      "L = 13.278020, acc = 0.960000\n",
      "L = 13.265865, acc = 0.960000\n",
      "L = 13.253759, acc = 0.960000\n",
      "L = 13.241700, acc = 0.960000\n",
      "L = 13.229689, acc = 0.960000\n",
      "L = 13.217726, acc = 0.960000\n",
      "L = 13.205809, acc = 0.960000\n",
      "L = 13.193939, acc = 0.960000\n",
      "L = 13.182115, acc = 0.960000\n",
      "L = 13.170338, acc = 0.960000\n",
      "L = 13.158606, acc = 0.960000\n",
      "L = 13.146920, acc = 0.960000\n",
      "L = 13.135279, acc = 0.960000\n",
      "L = 13.123684, acc = 0.960000\n",
      "L = 13.112133, acc = 0.960000\n",
      "L = 13.100626, acc = 0.960000\n",
      "L = 13.089164, acc = 0.960000\n",
      "L = 13.077746, acc = 0.965000\n",
      "L = 13.066371, acc = 0.965000\n",
      "L = 13.055040, acc = 0.965000\n",
      "L = 13.043752, acc = 0.965000\n",
      "L = 13.032507, acc = 0.965000\n",
      "L = 13.021304, acc = 0.965000\n",
      "L = 13.010144, acc = 0.965000\n",
      "L = 12.999026, acc = 0.965000\n",
      "L = 12.987949, acc = 0.965000\n",
      "L = 12.976914, acc = 0.965000\n",
      "L = 12.965921, acc = 0.965000\n",
      "L = 12.954969, acc = 0.965000\n",
      "L = 12.944057, acc = 0.965000\n",
      "L = 12.933186, acc = 0.965000\n",
      "L = 12.922356, acc = 0.965000\n",
      "L = 12.911565, acc = 0.965000\n",
      "L = 12.900814, acc = 0.965000\n",
      "L = 12.890103, acc = 0.965000\n",
      "L = 12.879432, acc = 0.965000\n",
      "L = 12.868799, acc = 0.965000\n",
      "L = 12.858206, acc = 0.965000\n",
      "L = 12.847651, acc = 0.965000\n",
      "L = 12.837134, acc = 0.965000\n",
      "L = 12.826656, acc = 0.965000\n",
      "L = 12.816215, acc = 0.965000\n",
      "L = 12.805813, acc = 0.965000\n",
      "L = 12.795448, acc = 0.965000\n",
      "L = 12.785120, acc = 0.965000\n",
      "L = 12.774829, acc = 0.965000\n",
      "L = 12.764575, acc = 0.965000\n",
      "L = 12.754358, acc = 0.965000\n",
      "L = 12.744177, acc = 0.965000\n",
      "L = 12.734032, acc = 0.965000\n",
      "L = 12.723923, acc = 0.965000\n",
      "L = 12.713850, acc = 0.965000\n",
      "L = 12.703813, acc = 0.965000\n",
      "L = 12.693810, acc = 0.965000\n",
      "L = 12.683843, acc = 0.965000\n",
      "L = 12.673911, acc = 0.965000\n",
      "L = 12.664014, acc = 0.965000\n",
      "L = 12.654150, acc = 0.965000\n",
      "L = 12.644322, acc = 0.965000\n",
      "L = 12.634527, acc = 0.965000\n",
      "L = 12.624766, acc = 0.965000\n",
      "L = 12.615039, acc = 0.965000\n",
      "L = 12.605345, acc = 0.965000\n",
      "L = 12.595685, acc = 0.965000\n",
      "L = 12.586058, acc = 0.965000\n",
      "L = 12.576463, acc = 0.965000\n",
      "L = 12.566901, acc = 0.965000\n",
      "L = 12.557372, acc = 0.965000\n",
      "L = 12.547875, acc = 0.965000\n",
      "L = 12.538410, acc = 0.965000\n",
      "L = 12.528977, acc = 0.965000\n",
      "L = 12.519576, acc = 0.965000\n",
      "L = 12.510206, acc = 0.965000\n",
      "L = 12.500867, acc = 0.965000\n",
      "L = 12.491560, acc = 0.965000\n",
      "L = 12.482284, acc = 0.965000\n",
      "L = 12.473038, acc = 0.965000\n",
      "L = 12.463823, acc = 0.965000\n",
      "L = 12.454639, acc = 0.965000\n",
      "L = 12.445485, acc = 0.965000\n",
      "L = 12.436360, acc = 0.965000\n",
      "L = 12.427266, acc = 0.965000\n",
      "L = 12.418202, acc = 0.965000\n",
      "L = 12.409167, acc = 0.965000\n",
      "L = 12.400161, acc = 0.965000\n",
      "L = 12.391184, acc = 0.965000\n",
      "L = 12.382237, acc = 0.965000\n",
      "L = 12.373318, acc = 0.965000\n",
      "L = 12.364429, acc = 0.965000\n",
      "L = 12.355567, acc = 0.965000\n",
      "L = 12.346734, acc = 0.965000\n",
      "L = 12.337929, acc = 0.965000\n",
      "L = 12.329152, acc = 0.965000\n",
      "L = 12.320403, acc = 0.965000\n",
      "L = 12.311682, acc = 0.965000\n",
      "L = 12.302988, acc = 0.965000\n",
      "L = 12.294322, acc = 0.965000\n",
      "L = 12.285682, acc = 0.965000\n",
      "L = 12.277070, acc = 0.965000\n",
      "L = 12.268485, acc = 0.965000\n",
      "L = 12.259926, acc = 0.965000\n",
      "L = 12.251394, acc = 0.965000\n",
      "L = 12.242889, acc = 0.965000\n",
      "L = 12.234409, acc = 0.965000\n",
      "L = 12.225956, acc = 0.965000\n",
      "L = 12.217529, acc = 0.965000\n",
      "L = 12.209127, acc = 0.965000\n",
      "L = 12.200751, acc = 0.965000\n",
      "L = 12.192401, acc = 0.965000\n",
      "L = 12.184076, acc = 0.965000\n",
      "L = 12.175776, acc = 0.965000\n",
      "L = 12.167502, acc = 0.965000\n",
      "L = 12.159252, acc = 0.965000\n",
      "L = 12.151027, acc = 0.965000\n",
      "L = 12.142826, acc = 0.965000\n",
      "L = 12.134650, acc = 0.965000\n",
      "L = 12.126499, acc = 0.965000\n",
      "L = 12.118371, acc = 0.965000\n",
      "L = 12.110268, acc = 0.965000\n",
      "L = 12.102188, acc = 0.965000\n",
      "L = 12.094133, acc = 0.965000\n",
      "L = 12.086101, acc = 0.965000\n",
      "L = 12.078092, acc = 0.965000\n",
      "L = 12.070107, acc = 0.965000\n",
      "L = 12.062145, acc = 0.965000\n",
      "L = 12.054206, acc = 0.965000\n",
      "L = 12.046290, acc = 0.965000\n",
      "L = 12.038397, acc = 0.965000\n",
      "L = 12.030527, acc = 0.965000\n",
      "L = 12.022679, acc = 0.965000\n",
      "L = 12.014854, acc = 0.965000\n",
      "L = 12.007051, acc = 0.965000\n",
      "L = 11.999270, acc = 0.965000\n",
      "L = 11.991511, acc = 0.965000\n",
      "L = 11.983774, acc = 0.965000\n",
      "L = 11.976059, acc = 0.965000\n",
      "L = 11.968365, acc = 0.965000\n",
      "L = 11.960693, acc = 0.965000\n",
      "L = 11.953043, acc = 0.965000\n",
      "L = 11.945414, acc = 0.965000\n",
      "L = 11.937805, acc = 0.965000\n",
      "L = 11.930218, acc = 0.965000\n",
      "L = 11.922652, acc = 0.965000\n",
      "L = 11.915107, acc = 0.965000\n",
      "L = 11.907582, acc = 0.965000\n",
      "L = 11.900078, acc = 0.965000\n",
      "L = 11.892594, acc = 0.965000\n",
      "L = 11.885131, acc = 0.965000\n",
      "L = 11.877688, acc = 0.965000\n",
      "L = 11.870265, acc = 0.965000\n",
      "L = 11.862862, acc = 0.965000\n",
      "L = 11.855479, acc = 0.965000\n",
      "L = 11.848115, acc = 0.965000\n",
      "L = 11.840771, acc = 0.965000\n",
      "L = 11.833447, acc = 0.965000\n",
      "L = 11.826142, acc = 0.965000\n",
      "L = 11.818856, acc = 0.965000\n",
      "L = 11.811590, acc = 0.965000\n",
      "L = 11.804342, acc = 0.965000\n",
      "L = 11.797114, acc = 0.965000\n",
      "L = 11.789904, acc = 0.965000\n",
      "L = 11.782713, acc = 0.965000\n",
      "L = 11.775541, acc = 0.965000\n",
      "L = 11.768387, acc = 0.965000\n",
      "L = 11.761252, acc = 0.965000\n",
      "L = 11.754135, acc = 0.965000\n",
      "L = 11.747036, acc = 0.965000\n",
      "L = 11.739956, acc = 0.965000\n",
      "L = 11.732893, acc = 0.965000\n",
      "L = 11.725848, acc = 0.965000\n",
      "L = 11.718821, acc = 0.965000\n",
      "L = 11.711812, acc = 0.965000\n",
      "L = 11.704820, acc = 0.965000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 11.697846, acc = 0.965000\n",
      "L = 11.690889, acc = 0.965000\n",
      "L = 11.683949, acc = 0.965000\n",
      "L = 11.677027, acc = 0.965000\n",
      "L = 11.670121, acc = 0.965000\n",
      "L = 11.663233, acc = 0.965000\n",
      "L = 11.656362, acc = 0.965000\n",
      "L = 11.649507, acc = 0.965000\n",
      "L = 11.642669, acc = 0.965000\n",
      "L = 11.635848, acc = 0.965000\n",
      "L = 11.629043, acc = 0.965000\n",
      "L = 11.622254, acc = 0.965000\n",
      "L = 11.615482, acc = 0.965000\n",
      "L = 11.608726, acc = 0.965000\n",
      "L = 11.601986, acc = 0.965000\n",
      "L = 11.595262, acc = 0.965000\n",
      "L = 11.588554, acc = 0.965000\n",
      "L = 11.581862, acc = 0.965000\n",
      "L = 11.575186, acc = 0.965000\n",
      "L = 11.568525, acc = 0.965000\n",
      "L = 11.561880, acc = 0.965000\n",
      "L = 11.555251, acc = 0.965000\n",
      "L = 11.548637, acc = 0.965000\n",
      "L = 11.542038, acc = 0.965000\n",
      "L = 11.535454, acc = 0.965000\n",
      "L = 11.528886, acc = 0.965000\n",
      "L = 11.522332, acc = 0.965000\n",
      "L = 11.515794, acc = 0.965000\n",
      "L = 11.509270, acc = 0.965000\n",
      "L = 11.502761, acc = 0.965000\n",
      "L = 11.496267, acc = 0.965000\n",
      "L = 11.489787, acc = 0.965000\n",
      "L = 11.483322, acc = 0.965000\n",
      "L = 11.476872, acc = 0.965000\n",
      "L = 11.470436, acc = 0.965000\n",
      "L = 11.464014, acc = 0.965000\n",
      "L = 11.457606, acc = 0.965000\n",
      "L = 11.451213, acc = 0.965000\n",
      "L = 11.444833, acc = 0.965000\n",
      "L = 11.438468, acc = 0.965000\n",
      "L = 11.432116, acc = 0.965000\n",
      "L = 11.425778, acc = 0.965000\n",
      "L = 11.419454, acc = 0.965000\n",
      "L = 11.413143, acc = 0.965000\n",
      "L = 11.406846, acc = 0.965000\n",
      "L = 11.400563, acc = 0.965000\n",
      "L = 11.394293, acc = 0.965000\n",
      "L = 11.388036, acc = 0.965000\n",
      "L = 11.381793, acc = 0.965000\n",
      "L = 11.375563, acc = 0.965000\n",
      "L = 11.369346, acc = 0.965000\n",
      "L = 11.363142, acc = 0.965000\n",
      "L = 11.356951, acc = 0.965000\n",
      "L = 11.350772, acc = 0.965000\n",
      "L = 11.344607, acc = 0.965000\n",
      "L = 11.338454, acc = 0.965000\n",
      "L = 11.332314, acc = 0.965000\n",
      "L = 11.326187, acc = 0.970000\n",
      "L = 11.320072, acc = 0.970000\n",
      "L = 11.313970, acc = 0.970000\n",
      "L = 11.307880, acc = 0.970000\n",
      "L = 11.301802, acc = 0.970000\n",
      "L = 11.295737, acc = 0.970000\n",
      "L = 11.289684, acc = 0.970000\n",
      "L = 11.283642, acc = 0.970000\n",
      "L = 11.277613, acc = 0.970000\n",
      "L = 11.271596, acc = 0.970000\n",
      "L = 11.265591, acc = 0.970000\n",
      "L = 11.259598, acc = 0.970000\n",
      "L = 11.253616, acc = 0.970000\n",
      "L = 11.247647, acc = 0.970000\n",
      "L = 11.241689, acc = 0.970000\n",
      "L = 11.235742, acc = 0.970000\n",
      "L = 11.229807, acc = 0.970000\n",
      "L = 11.223883, acc = 0.970000\n",
      "L = 11.217971, acc = 0.970000\n",
      "L = 11.212070, acc = 0.970000\n",
      "L = 11.206181, acc = 0.970000\n",
      "L = 11.200303, acc = 0.970000\n",
      "L = 11.194435, acc = 0.970000\n",
      "L = 11.188579, acc = 0.970000\n",
      "L = 11.182734, acc = 0.970000\n",
      "L = 11.176900, acc = 0.970000\n",
      "L = 11.171077, acc = 0.970000\n",
      "L = 11.165265, acc = 0.970000\n",
      "L = 11.159463, acc = 0.970000\n",
      "L = 11.153672, acc = 0.970000\n",
      "L = 11.147892, acc = 0.970000\n",
      "L = 11.142123, acc = 0.970000\n",
      "L = 11.136364, acc = 0.970000\n",
      "L = 11.130616, acc = 0.970000\n",
      "L = 11.124878, acc = 0.970000\n",
      "L = 11.119150, acc = 0.970000\n",
      "L = 11.113433, acc = 0.970000\n",
      "L = 11.107726, acc = 0.970000\n",
      "L = 11.102029, acc = 0.970000\n",
      "L = 11.096343, acc = 0.970000\n",
      "L = 11.090666, acc = 0.970000\n",
      "L = 11.085000, acc = 0.970000\n",
      "L = 11.079344, acc = 0.970000\n",
      "L = 11.073698, acc = 0.970000\n",
      "L = 11.068061, acc = 0.970000\n",
      "L = 11.062435, acc = 0.970000\n",
      "L = 11.056818, acc = 0.970000\n",
      "L = 11.051211, acc = 0.970000\n",
      "L = 11.045614, acc = 0.970000\n",
      "L = 11.040026, acc = 0.970000\n",
      "L = 11.034449, acc = 0.970000\n",
      "L = 11.028880, acc = 0.970000\n",
      "L = 11.023321, acc = 0.970000\n",
      "L = 11.017772, acc = 0.970000\n",
      "L = 11.012232, acc = 0.970000\n",
      "L = 11.006702, acc = 0.970000\n",
      "L = 11.001181, acc = 0.970000\n",
      "L = 10.995669, acc = 0.970000\n",
      "L = 10.990166, acc = 0.970000\n",
      "L = 10.984673, acc = 0.970000\n",
      "L = 10.979189, acc = 0.970000\n",
      "L = 10.973714, acc = 0.970000\n",
      "L = 10.968248, acc = 0.970000\n",
      "L = 10.962791, acc = 0.970000\n",
      "L = 10.957343, acc = 0.970000\n",
      "L = 10.951904, acc = 0.970000\n",
      "L = 10.946473, acc = 0.970000\n",
      "L = 10.941052, acc = 0.970000\n",
      "L = 10.935640, acc = 0.970000\n",
      "L = 10.930236, acc = 0.970000\n",
      "L = 10.924841, acc = 0.970000\n",
      "L = 10.919455, acc = 0.970000\n",
      "L = 10.914077, acc = 0.970000\n",
      "L = 10.908709, acc = 0.970000\n",
      "L = 10.903348, acc = 0.970000\n",
      "L = 10.897997, acc = 0.970000\n",
      "L = 10.892653, acc = 0.970000\n",
      "L = 10.887319, acc = 0.970000\n",
      "L = 10.881992, acc = 0.970000\n",
      "L = 10.876674, acc = 0.970000\n",
      "L = 10.871365, acc = 0.970000\n",
      "L = 10.866064, acc = 0.970000\n",
      "L = 10.860771, acc = 0.970000\n",
      "L = 10.855486, acc = 0.970000\n",
      "L = 10.850210, acc = 0.970000\n",
      "L = 10.844942, acc = 0.970000\n",
      "L = 10.839682, acc = 0.970000\n",
      "L = 10.834430, acc = 0.970000\n",
      "L = 10.829186, acc = 0.970000\n",
      "L = 10.823950, acc = 0.970000\n",
      "L = 10.818722, acc = 0.970000\n",
      "L = 10.813503, acc = 0.970000\n",
      "L = 10.808291, acc = 0.970000\n",
      "L = 10.803087, acc = 0.970000\n",
      "L = 10.797892, acc = 0.970000\n",
      "L = 10.792704, acc = 0.970000\n",
      "L = 10.787524, acc = 0.970000\n",
      "L = 10.782351, acc = 0.970000\n",
      "L = 10.777187, acc = 0.970000\n",
      "L = 10.772030, acc = 0.970000\n",
      "L = 10.766881, acc = 0.970000\n",
      "L = 10.761740, acc = 0.970000\n",
      "L = 10.756607, acc = 0.970000\n",
      "L = 10.751481, acc = 0.970000\n",
      "L = 10.746363, acc = 0.970000\n",
      "L = 10.741252, acc = 0.970000\n",
      "L = 10.736149, acc = 0.970000\n",
      "L = 10.731054, acc = 0.970000\n",
      "L = 10.725966, acc = 0.970000\n",
      "L = 10.720886, acc = 0.970000\n",
      "L = 10.715813, acc = 0.970000\n",
      "L = 10.710747, acc = 0.970000\n",
      "L = 10.705690, acc = 0.970000\n",
      "L = 10.700639, acc = 0.970000\n",
      "L = 10.695596, acc = 0.970000\n",
      "L = 10.690560, acc = 0.970000\n",
      "L = 10.685532, acc = 0.970000\n",
      "L = 10.680511, acc = 0.970000\n",
      "L = 10.675497, acc = 0.970000\n",
      "L = 10.670491, acc = 0.970000\n",
      "L = 10.665492, acc = 0.970000\n",
      "L = 10.660500, acc = 0.970000\n",
      "L = 10.655515, acc = 0.970000\n",
      "L = 10.650538, acc = 0.970000\n",
      "L = 10.645568, acc = 0.970000\n",
      "L = 10.640605, acc = 0.970000\n",
      "L = 10.635649, acc = 0.970000\n",
      "L = 10.630700, acc = 0.970000\n",
      "L = 10.625759, acc = 0.970000\n",
      "L = 10.620824, acc = 0.970000\n",
      "L = 10.615897, acc = 0.970000\n",
      "L = 10.610977, acc = 0.970000\n",
      "L = 10.606064, acc = 0.970000\n",
      "L = 10.601157, acc = 0.970000\n",
      "L = 10.596258, acc = 0.970000\n",
      "L = 10.591366, acc = 0.970000\n",
      "L = 10.586481, acc = 0.970000\n",
      "L = 10.581603, acc = 0.970000\n",
      "L = 10.576732, acc = 0.970000\n",
      "L = 10.571868, acc = 0.970000\n",
      "L = 10.567011, acc = 0.970000\n",
      "L = 10.562161, acc = 0.970000\n",
      "L = 10.557317, acc = 0.970000\n",
      "L = 10.552481, acc = 0.970000\n",
      "L = 10.547651, acc = 0.970000\n",
      "L = 10.542829, acc = 0.970000\n",
      "L = 10.538013, acc = 0.970000\n",
      "L = 10.533204, acc = 0.970000\n",
      "L = 10.528402, acc = 0.970000\n",
      "L = 10.523607, acc = 0.970000\n",
      "L = 10.518818, acc = 0.970000\n",
      "L = 10.514037, acc = 0.970000\n",
      "L = 10.509262, acc = 0.970000\n",
      "L = 10.504494, acc = 0.970000\n",
      "L = 10.499733, acc = 0.970000\n",
      "L = 10.494979, acc = 0.970000\n",
      "L = 10.490231, acc = 0.970000\n",
      "L = 10.485490, acc = 0.970000\n",
      "L = 10.480756, acc = 0.970000\n",
      "L = 10.476029, acc = 0.970000\n",
      "L = 10.471308, acc = 0.970000\n",
      "L = 10.466594, acc = 0.970000\n",
      "L = 10.461887, acc = 0.970000\n",
      "L = 10.457187, acc = 0.970000\n",
      "L = 10.452493, acc = 0.970000\n",
      "L = 10.447806, acc = 0.970000\n",
      "L = 10.443125, acc = 0.970000\n",
      "L = 10.438452, acc = 0.970000\n",
      "L = 10.433785, acc = 0.970000\n",
      "L = 10.429124, acc = 0.970000\n",
      "L = 10.424471, acc = 0.970000\n",
      "L = 10.419824, acc = 0.970000\n",
      "L = 10.415183, acc = 0.970000\n",
      "L = 10.410549, acc = 0.970000\n",
      "L = 10.405922, acc = 0.970000\n",
      "L = 10.401302, acc = 0.970000\n",
      "L = 10.396688, acc = 0.970000\n",
      "L = 10.392081, acc = 0.970000\n",
      "L = 10.387480, acc = 0.970000\n",
      "L = 10.382886, acc = 0.970000\n",
      "L = 10.378299, acc = 0.970000\n",
      "L = 10.373718, acc = 0.970000\n",
      "L = 10.369144, acc = 0.970000\n",
      "L = 10.364576, acc = 0.970000\n",
      "L = 10.360015, acc = 0.970000\n",
      "L = 10.355461, acc = 0.970000\n",
      "L = 10.350913, acc = 0.970000\n",
      "L = 10.346372, acc = 0.970000\n",
      "L = 10.341837, acc = 0.970000\n",
      "L = 10.337309, acc = 0.970000\n",
      "L = 10.332788, acc = 0.970000\n",
      "L = 10.328273, acc = 0.970000\n",
      "L = 10.323764, acc = 0.970000\n",
      "L = 10.319262, acc = 0.970000\n",
      "L = 10.314767, acc = 0.970000\n",
      "L = 10.310278, acc = 0.970000\n",
      "L = 10.305796, acc = 0.970000\n",
      "L = 10.301321, acc = 0.970000\n",
      "L = 10.296852, acc = 0.970000\n",
      "L = 10.292389, acc = 0.970000\n",
      "L = 10.287933, acc = 0.970000\n",
      "L = 10.283484, acc = 0.970000\n",
      "L = 10.279041, acc = 0.970000\n",
      "L = 10.274604, acc = 0.970000\n",
      "L = 10.270175, acc = 0.970000\n",
      "L = 10.265751, acc = 0.970000\n",
      "L = 10.261335, acc = 0.970000\n",
      "L = 10.256924, acc = 0.970000\n",
      "L = 10.252521, acc = 0.970000\n",
      "L = 10.248123, acc = 0.970000\n",
      "L = 10.243733, acc = 0.970000\n",
      "L = 10.239349, acc = 0.970000\n",
      "L = 10.234971, acc = 0.970000\n",
      "L = 10.230600, acc = 0.970000\n",
      "L = 10.226235, acc = 0.970000\n",
      "L = 10.221877, acc = 0.970000\n",
      "L = 10.217526, acc = 0.970000\n",
      "L = 10.213181, acc = 0.970000\n",
      "L = 10.208842, acc = 0.970000\n",
      "L = 10.204510, acc = 0.970000\n",
      "L = 10.200185, acc = 0.970000\n",
      "L = 10.195866, acc = 0.965000\n",
      "L = 10.191553, acc = 0.965000\n",
      "L = 10.187248, acc = 0.965000\n",
      "L = 10.182948, acc = 0.965000\n",
      "L = 10.178655, acc = 0.965000\n",
      "L = 10.174369, acc = 0.965000\n",
      "L = 10.170089, acc = 0.965000\n",
      "L = 10.165815, acc = 0.965000\n",
      "L = 10.161549, acc = 0.965000\n",
      "L = 10.157288, acc = 0.965000\n",
      "L = 10.153034, acc = 0.965000\n",
      "L = 10.148787, acc = 0.965000\n",
      "L = 10.144546, acc = 0.965000\n",
      "L = 10.140312, acc = 0.965000\n",
      "L = 10.136084, acc = 0.965000\n",
      "L = 10.131862, acc = 0.965000\n",
      "L = 10.127648, acc = 0.965000\n",
      "L = 10.123439, acc = 0.965000\n",
      "L = 10.119237, acc = 0.965000\n",
      "L = 10.115042, acc = 0.965000\n",
      "L = 10.110853, acc = 0.965000\n",
      "L = 10.106671, acc = 0.965000\n",
      "L = 10.102495, acc = 0.965000\n",
      "L = 10.098325, acc = 0.965000\n",
      "L = 10.094162, acc = 0.965000\n",
      "L = 10.090006, acc = 0.965000\n",
      "L = 10.085856, acc = 0.965000\n",
      "L = 10.081713, acc = 0.965000\n",
      "L = 10.077576, acc = 0.965000\n",
      "L = 10.073445, acc = 0.965000\n",
      "L = 10.069321, acc = 0.965000\n",
      "L = 10.065204, acc = 0.965000\n",
      "L = 10.061093, acc = 0.965000\n",
      "L = 10.056988, acc = 0.965000\n",
      "L = 10.052890, acc = 0.965000\n",
      "L = 10.048799, acc = 0.965000\n",
      "L = 10.044713, acc = 0.965000\n",
      "L = 10.040635, acc = 0.965000\n",
      "L = 10.036563, acc = 0.965000\n",
      "L = 10.032497, acc = 0.965000\n",
      "L = 10.028438, acc = 0.965000\n",
      "L = 10.024385, acc = 0.965000\n",
      "L = 10.020339, acc = 0.965000\n",
      "L = 10.016299, acc = 0.965000\n",
      "L = 10.012266, acc = 0.965000\n",
      "L = 10.008239, acc = 0.965000\n",
      "L = 10.004219, acc = 0.965000\n",
      "L = 10.000205, acc = 0.965000\n",
      "L = 9.996197, acc = 0.965000\n",
      "L = 9.992196, acc = 0.965000\n",
      "L = 9.988202, acc = 0.965000\n",
      "L = 9.984214, acc = 0.965000\n",
      "L = 9.980232, acc = 0.965000\n",
      "L = 9.976257, acc = 0.965000\n",
      "L = 9.972288, acc = 0.965000\n",
      "L = 9.968326, acc = 0.965000\n",
      "L = 9.964370, acc = 0.965000\n",
      "L = 9.960421, acc = 0.965000\n",
      "L = 9.956478, acc = 0.965000\n",
      "L = 9.952541, acc = 0.965000\n",
      "L = 9.948611, acc = 0.965000\n",
      "L = 9.944687, acc = 0.965000\n",
      "L = 9.940770, acc = 0.965000\n",
      "L = 9.936859, acc = 0.965000\n",
      "L = 9.932955, acc = 0.965000\n",
      "L = 9.929057, acc = 0.965000\n",
      "L = 9.925165, acc = 0.965000\n",
      "L = 9.921280, acc = 0.965000\n",
      "L = 9.917402, acc = 0.965000\n",
      "L = 9.913529, acc = 0.965000\n",
      "L = 9.909663, acc = 0.965000\n",
      "L = 9.905804, acc = 0.965000\n",
      "L = 9.901951, acc = 0.965000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "L = 9.898104, acc = 0.965000\n",
      "L = 9.894264, acc = 0.965000\n",
      "L = 9.890430, acc = 0.965000\n",
      "L = 9.886603, acc = 0.965000\n",
      "L = 9.882781, acc = 0.965000\n",
      "L = 9.878967, acc = 0.965000\n",
      "L = 9.875158, acc = 0.965000\n",
      "L = 9.871356, acc = 0.965000\n",
      "L = 9.867561, acc = 0.965000\n",
      "L = 9.863771, acc = 0.965000\n",
      "L = 9.859988, acc = 0.965000\n",
      "L = 9.856212, acc = 0.965000\n",
      "L = 9.852442, acc = 0.965000\n",
      "L = 9.848678, acc = 0.965000\n",
      "L = 9.844920, acc = 0.965000\n",
      "L = 9.841169, acc = 0.965000\n",
      "L = 9.837424, acc = 0.965000\n",
      "L = 9.833686, acc = 0.965000\n",
      "L = 9.829954, acc = 0.965000\n",
      "L = 9.826228, acc = 0.965000\n",
      "L = 9.822508, acc = 0.965000\n",
      "L = 9.818795, acc = 0.965000\n",
      "L = 9.815088, acc = 0.965000\n",
      "L = 9.811388, acc = 0.965000\n",
      "L = 9.807693, acc = 0.965000\n",
      "L = 9.804005, acc = 0.965000\n",
      "L = 9.800324, acc = 0.965000\n",
      "L = 9.796648, acc = 0.965000\n",
      "L = 9.792979, acc = 0.965000\n",
      "L = 9.789316, acc = 0.965000\n",
      "L = 9.785660, acc = 0.965000\n",
      "L = 9.782009, acc = 0.965000\n",
      "L = 9.778365, acc = 0.965000\n",
      "L = 9.774727, acc = 0.965000\n",
      "L = 9.771096, acc = 0.965000\n",
      "L = 9.767471, acc = 0.965000\n",
      "L = 9.763851, acc = 0.965000\n",
      "L = 9.760239, acc = 0.965000\n",
      "L = 9.756632, acc = 0.965000\n",
      "L = 9.753032, acc = 0.965000\n",
      "L = 9.749437, acc = 0.965000\n",
      "L = 9.745849, acc = 0.965000\n",
      "L = 9.742268, acc = 0.965000\n",
      "L = 9.738692, acc = 0.965000\n",
      "L = 9.735123, acc = 0.965000\n",
      "L = 9.731559, acc = 0.965000\n",
      "L = 9.728002, acc = 0.965000\n",
      "L = 9.724451, acc = 0.965000\n",
      "L = 9.720907, acc = 0.970000\n",
      "L = 9.717368, acc = 0.970000\n",
      "L = 9.713836, acc = 0.970000\n",
      "L = 9.710309, acc = 0.970000\n",
      "L = 9.706789, acc = 0.970000\n",
      "L = 9.703275, acc = 0.970000\n",
      "L = 9.699768, acc = 0.970000\n",
      "L = 9.696266, acc = 0.970000\n",
      "L = 9.692770, acc = 0.970000\n",
      "L = 9.689281, acc = 0.970000\n",
      "L = 9.685797, acc = 0.970000\n",
      "L = 9.682320, acc = 0.970000\n",
      "L = 9.678849, acc = 0.970000\n",
      "L = 9.675383, acc = 0.970000\n",
      "L = 9.671924, acc = 0.970000\n",
      "L = 9.668471, acc = 0.970000\n",
      "L = 9.665024, acc = 0.970000\n",
      "L = 9.661583, acc = 0.970000\n",
      "L = 9.658149, acc = 0.970000\n",
      "L = 9.654720, acc = 0.970000\n",
      "L = 9.651297, acc = 0.970000\n",
      "L = 9.647880, acc = 0.970000\n",
      "L = 9.644469, acc = 0.970000\n",
      "L = 9.641065, acc = 0.970000\n",
      "L = 9.637666, acc = 0.970000\n",
      "L = 9.634273, acc = 0.970000\n",
      "L = 9.630886, acc = 0.970000\n",
      "L = 9.627505, acc = 0.970000\n",
      "L = 9.624130, acc = 0.970000\n",
      "L = 9.620762, acc = 0.970000\n",
      "L = 9.617399, acc = 0.970000\n",
      "L = 9.614042, acc = 0.970000\n",
      "L = 9.610690, acc = 0.970000\n",
      "L = 9.607345, acc = 0.970000\n",
      "L = 9.604006, acc = 0.970000\n",
      "L = 9.600673, acc = 0.970000\n",
      "L = 9.597345, acc = 0.970000\n",
      "L = 9.594024, acc = 0.970000\n",
      "L = 9.590708, acc = 0.970000\n",
      "L = 9.587398, acc = 0.970000\n",
      "L = 9.584094, acc = 0.970000\n",
      "L = 9.580796, acc = 0.970000\n",
      "L = 9.577504, acc = 0.970000\n",
      "L = 9.574218, acc = 0.970000\n",
      "L = 9.570937, acc = 0.970000\n",
      "L = 9.567663, acc = 0.970000\n",
      "L = 9.564394, acc = 0.970000\n",
      "L = 9.561131, acc = 0.970000\n",
      "L = 9.557874, acc = 0.970000\n",
      "L = 9.554622, acc = 0.970000\n",
      "L = 9.551376, acc = 0.970000\n",
      "L = 9.548137, acc = 0.970000\n",
      "L = 9.544903, acc = 0.970000\n",
      "L = 9.541674, acc = 0.970000\n",
      "L = 9.538452, acc = 0.970000\n",
      "L = 9.535235, acc = 0.970000\n",
      "L = 9.532024, acc = 0.970000\n",
      "L = 9.528818, acc = 0.970000\n",
      "L = 9.525618, acc = 0.970000\n",
      "L = 9.522425, acc = 0.970000\n",
      "L = 9.519236, acc = 0.970000\n",
      "L = 9.516054, acc = 0.970000\n",
      "L = 9.512877, acc = 0.970000\n",
      "L = 9.509706, acc = 0.970000\n",
      "L = 9.506540, acc = 0.970000\n",
      "L = 9.503380, acc = 0.970000\n",
      "L = 9.500226, acc = 0.970000\n",
      "L = 9.497077, acc = 0.970000\n",
      "L = 9.493934, acc = 0.970000\n",
      "L = 9.490797, acc = 0.970000\n",
      "L = 9.487665, acc = 0.970000\n",
      "L = 9.484539, acc = 0.970000\n",
      "L = 9.481418, acc = 0.970000\n",
      "L = 9.478303, acc = 0.970000\n",
      "L = 9.475194, acc = 0.970000\n",
      "L = 9.472090, acc = 0.970000\n",
      "L = 9.468991, acc = 0.970000\n",
      "L = 9.465899, acc = 0.970000\n",
      "L = 9.462811, acc = 0.970000\n",
      "L = 9.459729, acc = 0.970000\n",
      "L = 9.456653, acc = 0.970000\n",
      "L = 9.453583, acc = 0.970000\n",
      "L = 9.450517, acc = 0.970000\n",
      "L = 9.447458, acc = 0.970000\n",
      "L = 9.444403, acc = 0.970000\n",
      "L = 9.441354, acc = 0.970000\n",
      "L = 9.438311, acc = 0.970000\n",
      "L = 9.435273, acc = 0.970000\n",
      "L = 9.432241, acc = 0.970000\n",
      "L = 9.429214, acc = 0.970000\n",
      "L = 9.426192, acc = 0.970000\n",
      "L = 9.423176, acc = 0.970000\n",
      "L = 9.420165, acc = 0.970000\n",
      "L = 9.417160, acc = 0.970000\n",
      "L = 9.414160, acc = 0.970000\n",
      "L = 9.411165, acc = 0.970000\n",
      "L = 9.408176, acc = 0.970000\n",
      "L = 9.405192, acc = 0.970000\n",
      "L = 9.402213, acc = 0.970000\n",
      "L = 9.399240, acc = 0.970000\n",
      "L = 9.396272, acc = 0.970000\n",
      "L = 9.393309, acc = 0.970000\n",
      "L = 9.390352, acc = 0.975000\n",
      "L = 9.387400, acc = 0.975000\n",
      "L = 9.384453, acc = 0.975000\n",
      "L = 9.381512, acc = 0.975000\n",
      "L = 9.378576, acc = 0.975000\n",
      "L = 9.375645, acc = 0.975000\n",
      "L = 9.372719, acc = 0.975000\n",
      "L = 9.369798, acc = 0.975000\n",
      "L = 9.366883, acc = 0.975000\n",
      "L = 9.363973, acc = 0.975000\n",
      "L = 9.361068, acc = 0.975000\n",
      "L = 9.358169, acc = 0.975000\n",
      "L = 9.355274, acc = 0.975000\n",
      "L = 9.352385, acc = 0.975000\n",
      "L = 9.349501, acc = 0.975000\n",
      "L = 9.346622, acc = 0.975000\n",
      "L = 9.343748, acc = 0.975000\n",
      "L = 9.340880, acc = 0.975000\n",
      "L = 9.338016, acc = 0.975000\n",
      "L = 9.335158, acc = 0.975000\n",
      "L = 9.332304, acc = 0.975000\n",
      "L = 9.329456, acc = 0.975000\n",
      "L = 9.326613, acc = 0.975000\n",
      "L = 9.323775, acc = 0.975000\n",
      "L = 9.320942, acc = 0.975000\n",
      "L = 9.318114, acc = 0.975000\n",
      "L = 9.315291, acc = 0.975000\n",
      "L = 9.312474, acc = 0.975000\n",
      "L = 9.309661, acc = 0.975000\n",
      "L = 9.306853, acc = 0.975000\n",
      "L = 9.304050, acc = 0.975000\n",
      "L = 9.301252, acc = 0.975000\n",
      "L = 9.298460, acc = 0.975000\n",
      "L = 9.295672, acc = 0.975000\n",
      "L = 9.292889, acc = 0.975000\n",
      "L = 9.290111, acc = 0.975000\n",
      "L = 9.287338, acc = 0.975000\n",
      "L = 9.284570, acc = 0.975000\n",
      "L = 9.281807, acc = 0.975000\n",
      "L = 9.279049, acc = 0.975000\n",
      "L = 9.276296, acc = 0.975000\n",
      "L = 9.273548, acc = 0.975000\n",
      "L = 9.270804, acc = 0.975000\n",
      "L = 9.268066, acc = 0.975000\n",
      "L = 9.265332, acc = 0.975000\n",
      "L = 9.262604, acc = 0.975000\n",
      "L = 9.259880, acc = 0.975000\n",
      "L = 9.257161, acc = 0.975000\n",
      "L = 9.254446, acc = 0.975000\n",
      "L = 9.251737, acc = 0.975000\n",
      "L = 9.249032, acc = 0.975000\n",
      "L = 9.246333, acc = 0.975000\n",
      "L = 9.243637, acc = 0.975000\n",
      "L = 9.240947, acc = 0.975000\n",
      "L = 9.238262, acc = 0.975000\n",
      "L = 9.235581, acc = 0.975000\n",
      "L = 9.232905, acc = 0.975000\n",
      "L = 9.230234, acc = 0.975000\n",
      "L = 9.227568, acc = 0.975000\n",
      "L = 9.224906, acc = 0.975000\n",
      "L = 9.222249, acc = 0.975000\n",
      "L = 9.219597, acc = 0.975000\n",
      "L = 9.216949, acc = 0.975000\n",
      "L = 9.214306, acc = 0.975000\n",
      "L = 9.211668, acc = 0.975000\n",
      "L = 9.209034, acc = 0.975000\n",
      "L = 9.206405, acc = 0.975000\n",
      "L = 9.203781, acc = 0.975000\n",
      "L = 9.201162, acc = 0.975000\n",
      "L = 9.198547, acc = 0.975000\n",
      "L = 9.195936, acc = 0.975000\n",
      "L = 9.193330, acc = 0.975000\n",
      "L = 9.190729, acc = 0.975000\n",
      "L = 9.188133, acc = 0.975000\n",
      "L = 9.185541, acc = 0.975000\n",
      "L = 9.182953, acc = 0.975000\n"
     ]
    }
   ],
   "source": [
    "# use the NN model and training\n",
    "nn = NN_Model([2, 8, 7, 2])\n",
    "nn.init_weight()\n",
    "nn.backpropagation(X, t, 2000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "5ac303e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# predict results & plot results\n",
    "y_res  = nn.forward(X)\n",
    "y_pred = np.argmax(y_res, axis=1)\n",
    "\n",
    "# plot data\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y, cmap=plt.cm.Spectral)\n",
    "plt.title(\"ground truth\")\n",
    "plt.show()\n",
    "\n",
    "plt.scatter(X[:, 0], X[:, 1], c=y_pred, cmap=plt.cm.Spectral)\n",
    "plt.title(\"predicted\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
